Search Results for author: Bo wang

Found 164 papers, 58 papers with code

TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph

no code implementations COLING 2022 Zhitong Yang, Bo wang, Jinfeng Zhou, Yue Tan, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou

We design a global reinforcement learning with the planned paths to flexibly adjust the local response generation model towards the global target.

Response Generation

CRFR: Improving Conversational Recommender Systems via Flexible Fragments Reasoning on Knowledge Graphs

no code implementations EMNLP 2021 Jinfeng Zhou, Bo wang, Ruifang He, Yuexian Hou

Although paths of user interests shift in knowledge graphs (KGs) can benefit conversational recommender systems (CRS), explicit reasoning on KGs has not been well considered in CRS, due to the complex of high-order and incomplete paths.

Knowledge Graphs Recommendation Systems +1

Have Seen Me Before? Automating Dataset Updates Towards Reliable and Timely Evaluation

no code implementations19 Feb 2024 Jiahao Ying, Yixin Cao, Bo wang, Wei Tang, Yizhe Yang, Shuicheng Yan

The basic idea is to generate unseen and high-quality testing samples based on existing ones to mitigate leakage issues.

Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces

no code implementations1 Feb 2024 Chloe Wang, Oleksii Tsepa, Jun Ma, Bo wang

Attention mechanisms have been widely used to capture long-range dependencies among nodes in Graph Transformers.

Computational Efficiency

Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data

1 code implementation31 Jan 2024 Congyu Fang, Adam Dziedzic, Lin Zhang, Laura Oliva, Amol Verma, Fahad Razak, Nicolas Papernot, Bo wang

In addition, the ML models trained with DeCaPH framework in general outperform those trained solely with the private datasets from individual parties, showing that DeCaPH enhances the model generalizability.

Mortality Prediction Privacy Preserving

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models

1 code implementation24 Jan 2024 Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo wang, Ruichao Yang

Then we propose to fine-tune a small language model as the debate judge for harmfulness inference, to facilitate multimodal fusion between the harmfulness rationales and the intrinsic multimodal information within memes.

Language Modelling Text Generation

ConvConcatNet: a deep convolutional neural network to reconstruct mel spectrogram from the EEG

no code implementations10 Jan 2024 Xiran Xu, Bo wang, Yujie Yan, Haolin Zhu, Zechen Zhang, Xihong Wu, Jing Chen

To investigate the processing of speech in the brain, simple linear models are commonly used to establish a relationship between brain signals and speech features.

EEG Task 2

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

no code implementations9 Jan 2024 Jun Ma, Feifei Li, Bo wang

Convolutional Neural Networks (CNNs) and Transformers have been the most popular architectures for biomedical image segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational complexity.

Cell Segmentation Image Segmentation +3

GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse

no code implementations3 Jan 2024 Hongzhan Lin, Ziyang Luo, Bo wang, Ruichao Yang, Jing Ma

The exponential growth of social media has profoundly transformed how information is created, disseminated, and absorbed, exceeding any precedent in the digital age.

Generative Pretraining at Scale: Transformer-Based Encoding of Transactional Behavior for Fraud Detection

no code implementations22 Dec 2023 Ze Yu Zhao, Zheng Zhu, Guilin Li, Wenhan Wang, Bo wang

In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems.

Anomaly Detection Fraud Detection

Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI

no code implementations17 Dec 2023 Qinqian Lei, Bo wang, Robby T. Tan

In our proposed method, we introduce novel label-uncertain query augmentation techniques to enhance the diversity of the query inputs, aiming to distinguish the positive HOI class from the negative ones.

Few-Shot Learning Human-Object Interaction Detection +1

Random resistive memory-based deep extreme point learning machine for unified visual processing

no code implementations14 Dec 2023 Shaocong Wang, Yizhao Gao, Yi Li, Woyu Zhang, Yifei Yu, Bo wang, Ning Lin, Hegan Chen, Yue Zhang, Yang Jiang, Dingchen Wang, Jia Chen, Peng Dai, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Xiaoxin Xu, Hayden So, Zhongrui Wang, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks.

Towards Verifiable Text Generation with Evolving Memory and Self-Reflection

no code implementations14 Dec 2023 Hao Sun, Hengyi Cai, Bo wang, Yingyan Hou, Xiaochi Wei, Shuaiqiang Wang, Yan Zhang, Dawei Yin

Despite the remarkable ability of large language models (LLMs) in language comprehension and generation, they often suffer from producing factually incorrect information, also known as hallucination.

Hallucination Retrieval +1

ShareCMP: Polarization-Aware RGB-P Semantic Segmentation

1 code implementation6 Dec 2023 Zhuoyan Liu, Bo wang, Lizhi Wang, Chenyu Mao, Ye Li

Multimodal semantic segmentation is developing rapidly, but the modality of RGB-Polarization remains underexplored.

Semantic Segmentation

Disordered hyperuniformity signals functioning and resilience of self-organized vegetation patterns

no code implementations13 Nov 2023 Wensi Hu, Quan-Xing Liu, Bo wang, Nuo Xu, Lijuan Cui, Chi Xu

Here we show that disordered hyperuniformity as a striking class of hidden orders can exist in spatially self-organized vegetation landscapes.

To Transformers and Beyond: Large Language Models for the Genome

no code implementations13 Nov 2023 Micaela E. Consens, Cameron Dufault, Michael Wainberg, Duncan Forster, Mehran Karimzadeh, Hani Goodarzi, Fabian J. Theis, Alan Moses, Bo wang

In the rapidly evolving landscape of genomics, deep learning has emerged as a useful tool for tackling complex computational challenges.

Splicing Up Your Predictions with RNA Contrastive Learning

1 code implementation12 Oct 2023 Philip Fradkin, Ruian Shi, Bo wang, Brendan Frey, Leo J. Lee

In the face of rapidly accumulating genomic data, our understanding of the RNA regulatory code remains incomplete.

Contrastive Learning Property Prediction +1

Lightweight Full-Convolutional Siamese Tracker

1 code implementation9 Oct 2023 Yunfeng Li, Bo wang, Xueyi Wu, Zhuoyan Liu, Ye Li

Although single object trackers have achieved advanced performance, their large-scale models hinder their application on limited resources platforms.

ORTexME: Occlusion-Robust Human Shape and Pose via Temporal Average Texture and Mesh Encoding

no code implementations21 Sep 2023 Yu Cheng, Bo wang, Robby T. Tan

In 3D human shape and pose estimation from a monocular video, models trained with limited labeled data cannot generalize well to videos with occlusion, which is common in the wild videos.

Neural Rendering Novel View Synthesis +1

A DenseNet-based method for decoding auditory spatial attention with EEG

1 code implementation14 Sep 2023 Xiran Xu, Bo wang, Yujie Yan, Xihong Wu, Jing Chen

ASAD methods are inspired by the brain lateralization of cortical neural responses during the processing of auditory spatial attention, and show promising performance for the task of auditory attention decoding (AAD) with neural recordings.

EEG

UnitModule: A Lightweight Joint Image Enhancement Module for Underwater Object Detection

no code implementations9 Sep 2023 Zhuoyan Liu, Bo wang, Ye Li, Jiaxian He, Yunfeng Li

In this paper, we propose a plug-and-play Underwater joint image enhancement Module (UnitModule) that provides the input image preferred by the detector.

Data Augmentation Image Enhancement +3

Mind vs. Mouth: On Measuring Re-judge Inconsistency of Social Bias in Large Language Models

no code implementations24 Aug 2023 Yachao Zhao, Bo wang, Dongming Zhao, Kun Huang, Yan Wang, Ruifang He, Yuexian Hou

We propose that this re-judge inconsistency can be similar to the inconsistency between human's unaware implicit social bias and their aware explicit social bias.

Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models

no code implementations20 Jul 2023 Michael Günther, Louis Milliken, Jonathan Geuter, Georgios Mastrapas, Bo wang, Han Xiao

Jina Embeddings constitutes a set of high-performance sentence embedding models adept at translating textual inputs into numerical representations, capturing the semantics of the text.

Negation Retrieval +5

Facilitating Multi-turn Emotional Support Conversation with Positive Emotion Elicitation: A Reinforcement Learning Approach

1 code implementation16 Jul 2023 Jinfeng Zhou, Zhuang Chen, Bo wang, Minlie Huang

Experiments verify the superiority of Supporter in achieving positive emotion elicitation during responding while maintaining conversational goals including coherence.

Magnetic Field-Based Reward Shaping for Goal-Conditioned Reinforcement Learning

no code implementations16 Jul 2023 Hongyu Ding, Yuanze Tang, Qing Wu, Bo wang, Chunlin Chen, Zhi Wang

Existing reward shaping methods for goal-conditioned RL are typically built on distance metrics with a linear and isotropic distribution, which may fail to provide sufficient information about the ever-changing environment with high complexity.

reinforcement-learning Reinforcement Learning (RL)

Training Physics-Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction

no code implementations8 Jul 2023 Bo wang, A. K. Qin, Sajjad Shafiei, Hussein Dia, Adriana-Simona Mihaita, Hanna Grzybowska

Physics-informed neural networks (PINNs) are a newly emerging research frontier in machine learning, which incorporate certain physical laws that govern a given data set, e. g., those described by partial differential equations (PDEs), into the training of the neural network (NN) based on such a data set.

SplatFlow: Learning Multi-frame Optical Flow via Splatting

no code implementations15 Jun 2023 Bo wang, Yifan Zhang, Jian Li, Yang Yu, Zhenping Sun, Li Liu, Dewen Hu

Occlusion problem remains a key challenge in Optical Flow Estimation (OFE) despite the recent significant progress brought by deep learning in the field.

Optical Flow Estimation

Spatially Resolved Gene Expression Prediction from H&E Histology Images via Bi-modal Contrastive Learning

1 code implementation2 Jun 2023 Ronald Xie, Kuan Pang, Sai W. Chung, Catia T. Perciani, Sonya A. MacParland, Bo wang, Gary D. Bader

Our results demonstrate the potential of BLEEP to provide insights into the molecular mechanisms underlying tissue architecture, with important implications in diagnosis and research of various diseases.

Benchmarking Contrastive Learning +1

CongFu: Conditional Graph Fusion for Drug Synergy Prediction

1 code implementation23 May 2023 Oleksii Tsepa, Bohdan Naida, Anna Goldenberg, Bo wang

Drug synergy, characterized by the amplified combined effect of multiple drugs, is critically important for optimizing therapeutic outcomes.

Decentralized Equalization for Massive MIMO Systems With Colored Noise Samples

no code implementations22 May 2023 Xiaotong Zhao, Mian Li, Bo wang, Enbin Song, Tsung-Hui Chang, Qingjiang Shi

However, current detection methods tailored to DBP only consider ideal white Gaussian noise scenarios, while in practice, the noise is often colored due to interference from neighboring cells.

Dimensionality Reduction

DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment

1 code implementation CVPR 2023 Heyuan Li, Bo wang, Yu Cheng, Mohan Kankanhalli, Robby T. Tan

Thanks to the proposed fusion module, our method is robust not only to occlusion and large pitch and roll view angles, which is the benefit of our image space approach, but also to noise and large yaw angles, which is the benefit of our model space method.

 Ranked #1 on 3D Face Reconstruction on AFLW2000-3D (Mean NME metric)

3D Face Reconstruction Face Alignment +1

Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona

1 code implementation19 May 2023 Yihong Tang, Bo wang, Miao Fang, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou

We design a Contrastive Latent Variable-based model (CLV) that clusters the dense persona descriptions into sparse categories, which are combined with the history query to generate personalized responses.

Dialogue Generation

Boosting Event Extraction with Denoised Structure-to-Text Augmentation

no code implementations16 May 2023 Bo wang, Heyan Huang, Xiaochi Wei, Ge Shi, Xiao Liu, Chong Feng, Tong Zhou, Shuaiqiang Wang, Dawei Yin

Event extraction aims to recognize pre-defined event triggers and arguments from texts, which suffer from the lack of high-quality annotations.

Event Extraction Text Augmentation +1

Segment Anything in Medical Images

2 code implementations24 Apr 2023 Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, Bo wang

Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring.

Image Segmentation Medical Image Segmentation +2

Time Reversal Enabled Fiber-Optic Time Synchronization

no code implementations14 Apr 2023 Yufeng Chen, Hongfei Dai, Wenlin Li, Fangmin Wang, Bo wang, Lijun Wang

It measures the clock difference between two locations without involving a data layer, which can reduce the complexity of the system.

Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations

1 code implementation9 Apr 2023 Tengfei Xu, Dachuan Liu, Peng Hao, Bo wang

We propose a novel paradigm that provides a unified framework of training neural operators and solving PDEs with the variational form, which we refer to as the variational operator learning (VOL).

Operator learning

Empathetic Response Generation via Emotion Cause Transition Graph

no code implementations23 Feb 2023 Yushan Qian, Bo wang, Ting-En Lin, Yinhe Zheng, Ying Zhu, Dongming Zhao, Yuexian Hou, Yuchuan Wu, Yongbin Li

Empathetic dialogue is a human-like behavior that requires the perception of both affective factors (e. g., emotion status) and cognitive factors (e. g., cause of the emotion).

Empathetic Response Generation Response Generation

Prescribed Time Time-varying Output Formation Tracking for Uncertain Heterogeneous Multi-agent Systems

no code implementations15 Feb 2023 Binghe An, Bo wang, Huijin Fan, Lei Liu, Yongji Wang

The time-varying output formation tracking for the heterogeneous multi-agent systems (MAS) is investigated in this paper.

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets

1 code implementation NeurIPS 2023 Lazar Atanackovic, Alexander Tong, Bo wang, Leo J. Lee, Yoshua Bengio, Jason Hartford

In this paper we leverage the fact that it is possible to estimate the "velocity" of gene expression with RNA velocity techniques to develop an approach that addresses both challenges.

Bayesian Inference Causal Discovery

NodeCoder: a graph-based machine learning platform to predict active sites of modeled protein structures

1 code implementation7 Feb 2023 Nasim Abdollahi, Seyed Ali Madani Tonekaboni, Jay Huang, Bo wang, Stephen MacKinnon

While accurate protein structure predictions are now available for nearly every observed protein sequence, predicted structures lack much of the functional context offered by experimental structure determination.

Think Twice: A Human-like Two-stage Conversational Agent for Emotional Response Generation

no code implementations12 Jan 2023 Yushan Qian, Bo wang, Shangzhao Ma, Wu Bin, Shuo Zhang, Dongming Zhao, Kun Huang, Yuexian Hou

Towards human-like dialogue systems, current emotional dialogue approaches jointly model emotion and semantics with a unified neural network.

Response Generation

Underwater Object Tracker: UOSTrack for Marine Organism Grasping of Underwater Vehicles

2 code implementations4 Jan 2023 Yunfeng Li, Bo wang, Ye Li, Zhuoyan Liu, Wei Huo, Yueming Li, Jian Cao

The UOHT training paradigm is designed to train the sample-imbalanced underwater tracker so that the tracker is exposed to a great number of underwater domain training samples and learns the feature expressions.

Data Augmentation Object +3

MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition

1 code implementation CVPR 2023 Ronald Xie, Kuan Pang, Gary D. Bader, Bo wang

Complete manual segmentation is unfeasible for large datasets, and while supervised methods have been proposed to automate segmentation, they often rely on manually generated ground truths which are especially challenging and time consuming to generate in biology due to the requirement of domain expertise.

Representation Learning Segmentation

Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval

no code implementations20 Dec 2022 John Giorgi, Luca Soldaini, Bo wang, Gary Bader, Kyle Lo, Lucy Lu Wang, Arman Cohan

Via extensive automatic and human evaluation, we determine: (1) state-of-the-art summarizers suffer large reductions in performance when applied to open-domain MDS, (2) additional training in the open-domain setting can reduce this sensitivity to imperfect retrieval, and (3) summarizers are insensitive to the retrieval of duplicate documents and the order of retrieved documents, but highly sensitive to other errors, like the retrieval of irrelevant documents.

Document Summarization Multi-Document Summarization +1

Overlapping oriented imbalanced ensemble learning method based on projective clustering and stagewise hybrid sampling

no code implementations30 Nov 2022 Fan Li, Bo wang, Pin Wang, Yongming Li

Secondly, according to the characteristics of subset classes, a stage-wise hybrid sampling algorithm is designed to realize the de-overlapping and balancing of subsets.

Clustering Ensemble Learning +1

Gradient Domain Weighted Guided Image Filtering

no code implementations30 Nov 2022 Bo wang, Yihong Wang, Xiubao Sui, YuAn Liu, Qian Chen

Guided image filter is a well-known local filter in image processing.

Image Denoising

CodeExp: Explanatory Code Document Generation

1 code implementation25 Nov 2022 Haotian Cui, Chenglong Wang, JunJie Huang, Jeevana Priya Inala, Todd Mytkowicz, Bo wang, Jianfeng Gao, Nan Duan

Our experiments show that (1) our refined training dataset lets models achieve better performance in the explanation generation tasks compared to larger unrefined data (15x larger), and (2) fine-tuned models can generate well-structured long docstrings comparable to human-written ones.

Explanation Generation Text Generation

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

4 code implementations9 Nov 2022 BigScience Workshop, :, Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, Jonathan Tow, Alexander M. Rush, Stella Biderman, Albert Webson, Pawan Sasanka Ammanamanchi, Thomas Wang, Benoît Sagot, Niklas Muennighoff, Albert Villanova del Moral, Olatunji Ruwase, Rachel Bawden, Stas Bekman, Angelina McMillan-Major, Iz Beltagy, Huu Nguyen, Lucile Saulnier, Samson Tan, Pedro Ortiz Suarez, Victor Sanh, Hugo Laurençon, Yacine Jernite, Julien Launay, Margaret Mitchell, Colin Raffel, Aaron Gokaslan, Adi Simhi, Aitor Soroa, Alham Fikri Aji, Amit Alfassy, Anna Rogers, Ariel Kreisberg Nitzav, Canwen Xu, Chenghao Mou, Chris Emezue, Christopher Klamm, Colin Leong, Daniel van Strien, David Ifeoluwa Adelani, Dragomir Radev, Eduardo González Ponferrada, Efrat Levkovizh, Ethan Kim, Eyal Bar Natan, Francesco De Toni, Gérard Dupont, Germán Kruszewski, Giada Pistilli, Hady Elsahar, Hamza Benyamina, Hieu Tran, Ian Yu, Idris Abdulmumin, Isaac Johnson, Itziar Gonzalez-Dios, Javier de la Rosa, Jenny Chim, Jesse Dodge, Jian Zhu, Jonathan Chang, Jörg Frohberg, Joseph Tobing, Joydeep Bhattacharjee, Khalid Almubarak, Kimbo Chen, Kyle Lo, Leandro von Werra, Leon Weber, Long Phan, Loubna Ben allal, Ludovic Tanguy, Manan Dey, Manuel Romero Muñoz, Maraim Masoud, María Grandury, Mario Šaško, Max Huang, Maximin Coavoux, Mayank Singh, Mike Tian-Jian Jiang, Minh Chien Vu, Mohammad A. Jauhar, Mustafa Ghaleb, Nishant Subramani, Nora Kassner, Nurulaqilla Khamis, Olivier Nguyen, Omar Espejel, Ona de Gibert, Paulo Villegas, Peter Henderson, Pierre Colombo, Priscilla Amuok, Quentin Lhoest, Rheza Harliman, Rishi Bommasani, Roberto Luis López, Rui Ribeiro, Salomey Osei, Sampo Pyysalo, Sebastian Nagel, Shamik Bose, Shamsuddeen Hassan Muhammad, Shanya Sharma, Shayne Longpre, Somaieh Nikpoor, Stanislav Silberberg, Suhas Pai, Sydney Zink, Tiago Timponi Torrent, Timo Schick, Tristan Thrush, Valentin Danchev, Vassilina Nikoulina, Veronika Laippala, Violette Lepercq, Vrinda Prabhu, Zaid Alyafeai, Zeerak Talat, Arun Raja, Benjamin Heinzerling, Chenglei Si, Davut Emre Taşar, Elizabeth Salesky, Sabrina J. Mielke, Wilson Y. Lee, Abheesht Sharma, Andrea Santilli, Antoine Chaffin, Arnaud Stiegler, Debajyoti Datta, Eliza Szczechla, Gunjan Chhablani, Han Wang, Harshit Pandey, Hendrik Strobelt, Jason Alan Fries, Jos Rozen, Leo Gao, Lintang Sutawika, M Saiful Bari, Maged S. Al-shaibani, Matteo Manica, Nihal Nayak, Ryan Teehan, Samuel Albanie, Sheng Shen, Srulik Ben-David, Stephen H. Bach, Taewoon Kim, Tali Bers, Thibault Fevry, Trishala Neeraj, Urmish Thakker, Vikas Raunak, Xiangru Tang, Zheng-Xin Yong, Zhiqing Sun, Shaked Brody, Yallow Uri, Hadar Tojarieh, Adam Roberts, Hyung Won Chung, Jaesung Tae, Jason Phang, Ofir Press, Conglong Li, Deepak Narayanan, Hatim Bourfoune, Jared Casper, Jeff Rasley, Max Ryabinin, Mayank Mishra, Minjia Zhang, Mohammad Shoeybi, Myriam Peyrounette, Nicolas Patry, Nouamane Tazi, Omar Sanseviero, Patrick von Platen, Pierre Cornette, Pierre François Lavallée, Rémi Lacroix, Samyam Rajbhandari, Sanchit Gandhi, Shaden Smith, Stéphane Requena, Suraj Patil, Tim Dettmers, Ahmed Baruwa, Amanpreet Singh, Anastasia Cheveleva, Anne-Laure Ligozat, Arjun Subramonian, Aurélie Névéol, Charles Lovering, Dan Garrette, Deepak Tunuguntla, Ehud Reiter, Ekaterina Taktasheva, Ekaterina Voloshina, Eli Bogdanov, Genta Indra Winata, Hailey Schoelkopf, Jan-Christoph Kalo, Jekaterina Novikova, Jessica Zosa Forde, Jordan Clive, Jungo Kasai, Ken Kawamura, Liam Hazan, Marine Carpuat, Miruna Clinciu, Najoung Kim, Newton Cheng, Oleg Serikov, Omer Antverg, Oskar van der Wal, Rui Zhang, Ruochen Zhang, Sebastian Gehrmann, Shachar Mirkin, Shani Pais, Tatiana Shavrina, Thomas Scialom, Tian Yun, Tomasz Limisiewicz, Verena Rieser, Vitaly Protasov, Vladislav Mikhailov, Yada Pruksachatkun, Yonatan Belinkov, Zachary Bamberger, Zdeněk Kasner, Alice Rueda, Amanda Pestana, Amir Feizpour, Ammar Khan, Amy Faranak, Ana Santos, Anthony Hevia, Antigona Unldreaj, Arash Aghagol, Arezoo Abdollahi, Aycha Tammour, Azadeh HajiHosseini, Bahareh Behroozi, Benjamin Ajibade, Bharat Saxena, Carlos Muñoz Ferrandis, Daniel McDuff, Danish Contractor, David Lansky, Davis David, Douwe Kiela, Duong A. Nguyen, Edward Tan, Emi Baylor, Ezinwanne Ozoani, Fatima Mirza, Frankline Ononiwu, Habib Rezanejad, Hessie Jones, Indrani Bhattacharya, Irene Solaiman, Irina Sedenko, Isar Nejadgholi, Jesse Passmore, Josh Seltzer, Julio Bonis Sanz, Livia Dutra, Mairon Samagaio, Maraim Elbadri, Margot Mieskes, Marissa Gerchick, Martha Akinlolu, Michael McKenna, Mike Qiu, Muhammed Ghauri, Mykola Burynok, Nafis Abrar, Nazneen Rajani, Nour Elkott, Nour Fahmy, Olanrewaju Samuel, Ran An, Rasmus Kromann, Ryan Hao, Samira Alizadeh, Sarmad Shubber, Silas Wang, Sourav Roy, Sylvain Viguier, Thanh Le, Tobi Oyebade, Trieu Le, Yoyo Yang, Zach Nguyen, Abhinav Ramesh Kashyap, Alfredo Palasciano, Alison Callahan, Anima Shukla, Antonio Miranda-Escalada, Ayush Singh, Benjamin Beilharz, Bo wang, Caio Brito, Chenxi Zhou, Chirag Jain, Chuxin Xu, Clémentine Fourrier, Daniel León Periñán, Daniel Molano, Dian Yu, Enrique Manjavacas, Fabio Barth, Florian Fuhrimann, Gabriel Altay, Giyaseddin Bayrak, Gully Burns, Helena U. Vrabec, Imane Bello, Ishani Dash, Jihyun Kang, John Giorgi, Jonas Golde, Jose David Posada, Karthik Rangasai Sivaraman, Lokesh Bulchandani, Lu Liu, Luisa Shinzato, Madeleine Hahn de Bykhovetz, Maiko Takeuchi, Marc Pàmies, Maria A Castillo, Marianna Nezhurina, Mario Sänger, Matthias Samwald, Michael Cullan, Michael Weinberg, Michiel De Wolf, Mina Mihaljcic, Minna Liu, Moritz Freidank, Myungsun Kang, Natasha Seelam, Nathan Dahlberg, Nicholas Michio Broad, Nikolaus Muellner, Pascale Fung, Patrick Haller, Ramya Chandrasekhar, Renata Eisenberg, Robert Martin, Rodrigo Canalli, Rosaline Su, Ruisi Su, Samuel Cahyawijaya, Samuele Garda, Shlok S Deshmukh, Shubhanshu Mishra, Sid Kiblawi, Simon Ott, Sinee Sang-aroonsiri, Srishti Kumar, Stefan Schweter, Sushil Bharati, Tanmay Laud, Théo Gigant, Tomoya Kainuma, Wojciech Kusa, Yanis Labrak, Yash Shailesh Bajaj, Yash Venkatraman, Yifan Xu, Yingxin Xu, Yu Xu, Zhe Tan, Zhongli Xie, Zifan Ye, Mathilde Bras, Younes Belkada, Thomas Wolf

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.

Language Modelling Multilingual NLP

Aligning Recommendation and Conversation via Dual Imitation

no code implementations5 Nov 2022 Jinfeng Zhou, Bo wang, Minlie Huang, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou

Human conversations of recommendation naturally involve the shift of interests which can align the recommendation actions and conversation process to make accurate recommendations with rich explanations.

Recommendation Systems

OSIC: A New One-Stage Image Captioner Coined

no code implementations4 Nov 2022 Bo wang, Zhao Zhang, Mingbo Zhao, Xiaojie Jin, Mingliang Xu, Meng Wang

To obtain rich features, we use the Swin Transformer to calculate multi-level features, and then feed them into a novel dynamic multi-sight embedding module to exploit both global structure and local texture of input images.

Descriptive Language Modelling +2

GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs

1 code implementation19 Oct 2022 Xin Liu, Xiaofei Shao, Bo wang, YaLi Li, Shengjin Wang

First, unlike previous methods, we leverage convolution neural networks as well as graph neural networks in a complementary way for geometric representation learning.

Autonomous Driving Depth Completion +1

Bottom-Up 2D Pose Estimation via Dual Anatomical Centers for Small-Scale Persons

no code implementations25 Aug 2022 Yu Cheng, Yihao Ai, Bo wang, Xinchao Wang, Robby T. Tan

In multi-person 2D pose estimation, the bottom-up methods simultaneously predict poses for all persons, and unlike the top-down methods, do not rely on human detection.

2D Pose Estimation Human Detection +1

CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation

1 code implementation18 Aug 2022 Jinfeng Zhou, Chujie Zheng, Bo wang, Zheng Zhang, Minlie Huang

Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy.

Dialogue Generation Empathetic Response Generation +1

Fisher Matrix Based Fault Detection for PMUs Data in Power Grids

no code implementations9 Aug 2022 Ke Chen, Dandan Jiang, Bo wang, Hongxia Wang

Firstly, the fault detection matrix is constructed and the event detection problem is reformatted as a two-sample covariance matrices test problem.

Event Detection Fault Detection +1

Template-based Abstractive Microblog Opinion Summarisation

no code implementations8 Aug 2022 Iman Munire Bilal, Bo wang, Adam Tsakalidis, Dong Nguyen, Rob Procter, Maria Liakata

We introduce the task of microblog opinion summarisation (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain.

Cycle Self-Training for Semi-Supervised Object Detection with Distribution Consistency Reweighting

no code implementations12 Jul 2022 Hao liu, Bin Chen, Bo wang, Chunpeng Wu, Feng Dai, Peng Wu

To address the coupling problem, we propose a Cycle Self-Training (CST) framework for SSOD, which consists of two teachers T1 and T2, two students S1 and S2.

object-detection Object Detection +1

Underactuated Source Seeking by Surge Force Tuning: Theory and Boat Experiments

no code implementations9 May 2022 Bo wang, Sergey Nersesov, Hashem Ashrafiuon, Peiman Naseradinmousavi, Miroslav Krstić

We extend source seeking algorithms, in the absence of position and velocity measurements, and with tuning of the surge input, from velocity-actuated (unicycle) kinematic models to force-actuated generic Euler-Lagrange dynamic underactuated models.

Position

Dual networks based 3D Multi-Person Pose Estimation from Monocular Video

1 code implementation2 May 2022 Yu Cheng, Bo wang, Robby T. Tan

Most of the methods focus on single persons, which estimate the poses in the person-centric coordinates, i. e., the coordinates based on the center of the target person.

3D Multi-Person Pose Estimation (absolute) 3D Multi-Person Pose Estimation (root-relative) +4

A sequence-to-sequence approach for document-level relation extraction

2 code implementations BioNLP (ACL) 2022 John Giorgi, Gary D. Bader, Bo wang

In this paper, we develop a sequence-to-sequence approach, seq2rel, that can learn the subtasks of DocRE (entity extraction, coreference resolution and relation extraction) end-to-end, replacing a pipeline of task-specific components.

coreference-resolution Document-level Relation Extraction +3

Hybrid Routing Transformer for Zero-Shot Learning

no code implementations29 Mar 2022 De Cheng, Gerong Wang, Bo wang, Qiang Zhang, Jungong Han, Dingwen Zhang

This design makes the presented transformer model a hybrid of 1) top-down and bottom-up attention pathways and 2) dynamic and static routing pathways.

Attribute Zero-Shot Learning

Interactive Image Synthesis with Panoptic Layout Generation

1 code implementation CVPR 2022 Bo wang, Tao Wu, Minfeng Zhu, Peng Du

In particular, the stuff layouts can take amorphous shapes and fill up the missing regions left out by the instance layouts.

Layout-to-Image Generation

MHSnet: Multi-head and Spatial Attention Network with False-Positive Reduction for Pulmonary Nodules Detection

no code implementations31 Jan 2022 Juanyun Mai, Minghao Wang, Jiayin Zheng, Yanbo Shao, Zhaoqi Diao, Xinliang Fu, Yulong Chen, Jianyu Xiao, Jian You, Airu Yin, Yang Yang, Xiangcheng Qiu, Jinsheng Tao, Bo wang, Hua Ji

The false positive reduction module significantly decreases the average number of candidates generated per scan by 68. 11% and the false discovery rate by 13. 48%, which is promising to reduce distracted proposals for the downstream tasks based on the detection results.

Head Detection

Neural-FST Class Language Model for End-to-End Speech Recognition

no code implementations28 Jan 2022 Antoine Bruguier, Duc Le, Rohit Prabhavalkar, Dangna Li, Zhe Liu, Bo wang, Eun Chang, Fuchun Peng, Ozlem Kalinli, Michael L. Seltzer

We propose Neural-FST Class Language Model (NFCLM) for end-to-end speech recognition, a novel method that combines neural network language models (NNLMs) and finite state transducers (FSTs) in a mathematically consistent framework.

Language Modelling speech-recognition +1

Random cohort effects and age groups dependency structure for mortality modelling and forecasting: Mixed-effects time-series model approach

no code implementations31 Dec 2021 Ka Kin Lam, Bo wang

There have been significant efforts devoted to solving the longevity risk given that a continuous growth in population ageing has become a severe issue for many developed countries over the past few decades.

Time Series Time Series Analysis

High-Fidelity Point Cloud Completion with Low-Resolution Recovery and Noise-Aware Upsampling

no code implementations21 Dec 2021 Ren-Wu Li, Bo wang, Chun-Peng Li, Ling-Xiao Zhang, Lin Gao

Instead of decoding a whole shape, we propose to decode and refine a low-resolution (low-res) point cloud first, and then performs a patch-wise noise-aware upsampling rather than interpolating the whole sparse point cloud at once, which tends to lose details.

Point Cloud Completion

Comparison between Time Shifting Deviation and Cross-correlation Methods

no code implementations15 Nov 2021 Zhongwang Pang, Guan Wang, Bo wang, Lijun Wang

It stands in clear contrast to the result of cross-correlation method, whose localization error is 70 m and the standard deviation is 208. 4 m. Compared with cross-correlation method, TSDEV has the same resistance to white noise, but has fewer boundary conditions and better suppression on linear drift or common noise, which leads to more precise TDE results.

Traffic4cast -- Large-scale Traffic Prediction using 3DResNet and Sparse-UNet

1 code implementation10 Nov 2021 Bo wang, Reza Mohajerpoor, Chen Cai, Inhi Kim, Hai L. Vu

The aim is to build a machine learning model for predicting the normalized average traffic speed and flow of the subregions of multiple large-scale cities using historical data points.

Traffic Prediction

MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers

2 code implementations8 Nov 2021 Adamo Young, Bo wang, Hannes Röst

MassFormer outperforms competing approaches for spectrum prediction on multiple datasets, and is able to recover prior knowledge about the effect of collision energy on the spectrum.

Drug Discovery

OctField: Hierarchical Implicit Functions for 3D Modeling

no code implementations NeurIPS 2021 Jia-Heng Tang, Weikai Chen, Jie Yang, Bo wang, Songrun Liu, Bo Yang, Lin Gao

We achieve this goal by introducing a hierarchical octree structure to adaptively subdivide the 3D space according to the surface occupancy and the richness of part geometry.

Rethinking Lightweight Convolutional Neural Networks for Efficient and High-quality Pavement Crack Detection

2 code implementations13 Sep 2021 Kai Li, Jie Yang, Siwei Ma, Bo wang, Shanshe Wang, Yingjie Tian, Zhiquan Qi

For the second issue, we reconsider how to improve detection efficiency with excellent performance, and then propose our lightweight encoder-decoder architecture termed CarNet.

A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis

no code implementations3 Sep 2021 Dimitris Gkoumas, Bo wang, Adam Tsakalidis, Maria Wolters, Arkaitz Zubiaga, Matthew Purver, Maria Liakata

The corpus consists of spoken conversations, a subset of which are transcribed, as well as typed and written thoughts and associated extra-linguistic information such as pen strokes and keystrokes.

Transferring Knowledge Distillation for Multilingual Social Event Detection

1 code implementation6 Aug 2021 Jiaqian Ren, Hao Peng, Lei Jiang, Jia Wu, Yongxin Tong, Lihong Wang, Xu Bai, Bo wang, Qiang Yang

Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce.

Cross-Lingual Word Embeddings Event Detection +2

Evaluation of Thematic Coherence in Microblogs

no code implementations ACL 2021 Iman Munire Bilal, Bo wang, Maria Liakata, Rob Procter, Adam Tsakalidis

Here we create a corpus of microblog clusters from three different domains and time windows and define the task of evaluating thematic coherence.

Text Generation

Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function

no code implementations29 Jun 2021 Kai Li, Bo wang, Yingjie Tian, Zhiquan Qi

Numerous detection problems in computer vision, including road crack detection, suffer from exceedingly foreground-background imbalance.

Two-stage Training for Learning from Label Proportions

no code implementations22 May 2021 Jiabin Liu, Bo wang, Xin Shen, Zhiquan Qi, Yingjie Tian

Learning from label proportions (LLP) aims at learning an instance-level classifier with label proportions in grouped training data.

Vocal Bursts Valence Prediction

Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks

1 code implementation CVPR 2021 Yu Cheng, Bo wang, Bo Yang, Robby T. Tan

Besides the integration of top-down and bottom-up networks, unlike existing pose discriminators that are designed solely for single person, and consequently cannot assess natural inter-person interactions, we propose a two-person pose discriminator that enforces natural two-person interactions.

3D Multi-Person Pose Estimation (absolute) 3D Multi-Person Pose Estimation (root-relative) +2

Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images

1 code implementation29 Mar 2021 Dingwen Zhang, Bo wang, Gerong Wang, Qiang Zhang, Jiajia Zhang, Jungong Han, Zheng You

Onfocus detection aims at identifying whether the focus of the individual captured by a camera is on the camera or not.

Auditory Attention Decoding from EEG using Convolutional Recurrent Neural Network

no code implementations3 Mar 2021 Zhen Fu, Bo wang, Xihong Wu, Jing Chen

In this paper, we proposed novel convolutional recurrent neural network (CRNN) based regression model and classification model, and compared them with both the linear model and the state-of-the-art DNN models.

Classification EEG +3

Continuous quantum light from a dark atom

no code implementations1 Mar 2021 Karl Nicolas Tolazzi, Bo wang, Christopher Ianzano, Jonas Neumeier, Celso Jorge Villas-Boas, Gerhard Rempe

Cycling processes are important in many areas of physics ranging from lasers to topological insulators, often offering surprising insights into dynamical and structural aspects of the respective system.

Quantum Physics

Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder

no code implementations18 Feb 2021 Bo wang, Yue Wu, Nemanja Vaci, Maria Liakata, Terry Lyons, Kate E A Saunders

Bipolar disorder (BD) and borderline personality disorder (BPD) are two chronic mental health conditions that clinicians find challenging to distinguish based on clinical interviews, due to their overlapping symptoms.

Robust non-parametric mortality and fertility modelling and forecasting: Gaussian process regression approaches

no code implementations18 Feb 2021 Ka Kin Lam, Bo wang

A rapid decline in mortality and fertility has become major issues in many developed countries over the past few decades.

Decision Making regression

Multipopulation mortality modelling and forecasting: The multivariate functional principal component with time weightings approaches

no code implementations18 Feb 2021 Ka Kin Lam, Bo wang

The first model extends the independent functional data model to a multi-population modelling setting.

The effect of aspherical stellar wind of giant stars on the symbiotic channel of type Ia supernovae

no code implementations18 Feb 2021 Chengyuan Wu, Dongdong Liu, XiaoFeng Wang, Bo wang

The progenitor systems accounting for explosions of type Ia supernovae (SNe Ia) is still under debate.

Solar and Stellar Astrophysics

Spectrum of the doubly charmed molecular pentaquarks in chiral effective field theory

no code implementations11 Feb 2021 Kan Chen, Bo wang, Shi-Lin Zhu

We perform a systematic study on the interactions of the $\Sigma_c^{(*)}D^{(*)}$ systems within the framework of chiral effective field theory.

High Energy Physics - Phenomenology High Energy Physics - Experiment High Energy Physics - Lattice Nuclear Theory

Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection

no code implementations27 Jan 2021 Yuxiang Ren, Bo wang, Jiawei Zhang, Yi Chang

AA-HGNN utilizes an active learning framework to enhance learning performance, especially when facing the paucity of labeled data.

Active Learning Fake News Detection +2

Optimizing Biomanufacturing Harvesting Decisions under Limited Historical Data

no code implementations11 Jan 2021 Bo wang, Wei Xie, Tugce Martagan, Alp Akcay, Bram van Ravenstein

We adopt a Bayesian approach to update the unknown parameters of the growth-rate distributions, and use the resulting posterior distributions to characterize the impact of model risk on fermentation output variability.

Decision Making Model-based Reinforcement Learning

OT-LLP: Optimal Transport for Learning from Label Proportions

no code implementations1 Jan 2021 Jiabin Liu, Hanyuan Hang, Bo wang, Xin Shen, Zhouchen Lin

Learning from label proportions (LLP), where the training data are arranged in form of groups with only label proportions provided instead of the exact labels, is an important weakly supervised learning paradigm in machine learning.

Weakly-supervised Learning

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos

1 code implementation22 Dec 2020 Yu Cheng, Bo wang, Bo Yang, Robby T. Tan

To tackle this problem, we propose a novel framework integrating graph convolutional networks (GCNs) and temporal convolutional networks (TCNs) to robustly estimate camera-centric multi-person 3D poses that do not require camera parameters.

3D Absolute Human Pose Estimation 3D Multi-Person Pose Estimation (absolute) +5

Predicting the $\bar{D}_s^{(*)} D_s^{(*)}$ bound states as the partners of $X(3872)$

no code implementations17 Dec 2020 Lu Meng, Bo wang, Shi-Lin Zhu

We prove the existence of the $[\bar{D}_{s}^{*}D_{s}^{*}]^{0^{++}}$, $[\bar{D}_{s}^{*}D_{s}/\bar{D}_{s}^{}D_{s}^*]^{1^{+-}}$, and $[\bar{D}_{s}^{*}D_{s}^{*}]^{1^{+-}}$ bound states as the consequence of two prerequisites in the SU(3) flavor symmetry and heavy quark spin symmetry.

High Energy Physics - Phenomenology High Energy Physics - Experiment High Energy Physics - Lattice

Information Extraction from Swedish Medical Prescriptions with Sig-Transformer Encoder

no code implementations EMNLP (ClinicalNLP) 2020 John Pougue Biyong, Bo wang, Terry Lyons, Alejo J Nevado-Holgado

Relying on large pretrained language models such as Bidirectional Encoder Representations from Transformers (BERT) for encoding and adding a simple prediction layer has led to impressive performance in many clinical natural language processing (NLP) tasks.

Sound speed resonance of the stochastic gravitational wave background

no code implementations21 Sep 2020 Yi-Fu Cai, Chunshan Lin, Bo wang, Sheng-Feng Yan

We propose a novel mechanism to amplify the primordial gravitational waves (GWs) at the scale which can be detected by current or near future gravitational wave detectors.

General Relativity and Quantum Cosmology Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology High Energy Physics - Theory

Integrated Longitudinal Speed Decision-Making and Energy Efficiency Control for Connected Electrified Vehicles

no code implementations24 Jul 2020 Teng Liu, Bo wang, Dongpu Cao, Xiaolin Tang, Yalian Yang

As the core of this study, model predictive control and reinforcement learning are combined to improve the powertrain mobility and fuel economy for a group of automated vehicles.

Autonomous Vehicles Decision Making +3

DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations

2 code implementations ACL 2021 John Giorgi, Osvald Nitski, Bo wang, Gary Bader

Inspired by recent advances in deep metric learning (DML), we carefully design a self-supervised objective for learning universal sentence embeddings that does not require labelled training data.

Clustering Contrastive Learning +6

Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion

1 code implementation30 Apr 2020 Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Yi Chang

In experiments, we achieve state-of-the-art performance on three benchmarks and a zero-shot dataset for link prediction, with highlights of inference costs reduced by 1-2 orders of magnitude compared to a textual encoding method.

Graph Embedding Link Prediction +1

COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution

no code implementations23 Apr 2020 Qingsen Yan, Bo wang, Dong Gong, Chuan Luo, Wei Zhao, Jianhu Shen, Qinfeng Shi, Shuo Jin, Liang Zhang, Zheng You

Inspired by the observation that the boundary of the infected lung can be enhanced by adjusting the global intensity, in the proposed deep CNN, we introduce a feature variation block which adaptively adjusts the global properties of the features for segmenting COVID-19 infection.

Computed Tomography (CT) Image Segmentation +3

A Novel CNN-based Method for Accurate Ship Detection in HR Optical Remote Sensing Images via Rotated Bounding Box

1 code implementation15 Apr 2020 Linhao Li, Zhiqiang Zhou, Bo wang, Lingjuan Miao, Hua Zong

By contrast, we are able to predict the orientation and other variables independently, and yet more effectively, with a novel dual-branch regression network, based on the observation that the ship targets are nearly rotation-invariant in remote sensing images.

regression

SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation

3 code implementations21 Jan 2020 Jesse Sun, Fatemeh Darbehani, Mark Zaidi, Bo wang

Despite the progress of deep learning in medical image segmentation, standard CNNs are still not fully adopted in clinical settings as they lack robustness and interpretability.

Image Segmentation Medical Image Segmentation +2

Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks

no code implementations5 Jan 2020 Zhiyong Dou, Haotian Cui, Lin Zhang, Bo wang

Diffusion has shown great success in improving accuracy of unsupervised image retrieval systems by utilizing high-order structures of image manifold.

Image Retrieval Retrieval

Diversity Transfer Network for Few-Shot Learning

1 code implementation31 Dec 2019 Mengting Chen, Yuxin Fang, Xinggang Wang, Heng Luo, Yifeng Geng, Xin-Yu Zhang, Chang Huang, Wenyu Liu, Bo wang

The learning problem of the sample generation (i. e., diversity transfer) is solved via minimizing an effective meta-classification loss in a single-stage network, instead of the generative loss in previous works.

Few-Shot Learning

End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models

1 code implementation20 Dec 2019 John Giorgi, Xindi Wang, Nicola Sahar, Won Young Shin, Gary D. Bader, Bo wang

In this paper, we propose a neural, end-to-end model for jointly extracting entities and their relations which does not rely on external NLP tools and which integrates a large, pre-trained language model.

Language Modelling named-entity-recognition +5

Shenjing: A low power reconfigurable neuromorphic accelerator with partial-sum and spike networks-on-chip

1 code implementation25 Nov 2019 Bo Wang, Jun Zhou, Weng-Fai Wong, Li-Shiuan Peh

We show that conventional artificial neural networks (ANN) such as multilayer perceptron, convolutional neural networks, as well as the latest residual neural networks can be mapped successfully onto Shenjing, realizing ANNs with SNN's energy efficiency.

DeepGeneMD: A Joint Deep Learning Model for Extracting Gene Mutation-Disease Knowledge from PubMed Literature

no code implementations WS 2019 Feifan Liu, Xiaoyu Zheng, Bo wang, Catarina Kiefe

Understanding the pathogenesis of genetic diseases through different gene activities and their relations to relevant diseases is important for new drug discovery and drug repositioning.

Drug Discovery Multi-Task Learning +4

s-LWSR: Super Lightweight Super-Resolution Network

1 code implementation24 Sep 2019 Biao Li, Jiabin Liu, Bo Wang, Zhiquan Qi, Yong Shi

Deep learning (DL) architectures for superresolution (SR) normally contain tremendous parameters, which has been regarded as the crucial advantage for obtaining satisfying performance.

Super-Resolution

Interpretable Biomanufacturing Process Risk and Sensitivity Analyses for Quality-by-Design and Stability Control

no code implementations10 Sep 2019 Wei Xie, Bo wang, Cheng Li, Dongming Xie, Jared Auclair

While biomanufacturing plays a significant role in supporting the economy and ensuring public health, it faces critical challenges, including complexity, high variability, lengthy lead time, and very limited process data, especially for personalized new cell and gene biotherapeutics.

Learning from Label Proportions with Generative Adversarial Networks

1 code implementation NeurIPS 2019 Jiabin Liu, Bo wang, Zhiquan Qi, Yingjie Tian, Yong Shi

In this paper, we leverage generative adversarial networks (GANs) to derive an effective algorithm LLP-GAN for learning from label proportions (LLP), where only the bag-level proportional information in labels is available.

Deep Differentiable Random Forests for Age Estimation

no code implementations23 Jul 2019 Wei Shen, Yilu Guo, Yan Wang, Kai Zhao, Bo wang, Alan Yuille

Both of them connect split nodes to the top layer of convolutional neural networks (CNNs) and deal with inhomogeneous data by jointly learning input-dependent data partitions at the split nodes and age distributions at the leaf nodes.

Age Estimation regression

A Minimax Game for Instance based Selective Transfer Learning

no code implementations1 Jul 2019 Bo wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jung Huang, Bo Zheng, Deng Cai, Jingren Zhou

To the best of our knowledge, this is the first to build a minimax game based model for selective transfer learning.

Retrieval Text Retrieval +1

Companion Surface of Danger Cylinder and its Role in Solution Variation of P3P Problem

no code implementations4 Jun 2019 Bo wang, Hao Hu, Caixia Zhang

And when the optical center moves on the danger cylinder, accordingly the optical centers of the two other solutions of the corresponding P3P problem form a new surface, characterized by a polynomial equation of degree 12 in the optical center coordinates, called the Companion Surface of Danger Cylinder (CSDC).

Can We Derive Explicit and Implicit Bias from Corpus?

no code implementations31 May 2019 Bo Wang, Baixiang Xue, Anthony G. Greenwald

Inspired by psychological measurements of explicit and implicit bias, we develop an automatic language-based technique to reproduce psychological measurements on large population.

New insights on Multi-Solution Distribution of the P3P Problem

no code implementations30 Jan 2019 Bo Wang, Hao Hu, Caixia Zhang

In this work, we show that when the optical center is outside of all the 6 toroids defined by the control point triangle, each positive root of the Grunert's quartic equation must correspond to a true solution of the P3P problem, and the corresponding P3P problem cannot have a unique solution, it must have either 2 positive solutions or 4 positive solutions.

Geometric Interpretation of side-sharing and point-sharing solutions in the P3P Problem

no code implementations29 Jan 2019 Bo wang, Hao Hu, Caixia Zhang

In this work, we provide some new geometric interpretations on the multi-solution phenomenon in the P3P problem, our main results include: (1): The necessary and sufficient condition for the P3P problem to have a pair of side-sharing solutions is the two optical centers of the solutions both lie on one of the 3 vertical planes to the base plane of control points; (2): The necessary and sufficient condition for the P3P problem to have a pair of point-sharing solutions is the two optical centers of the solutions both lie on one of the 3 so-called skewed danger cylinders;(3): If the P3P problem has other solutions in addition to a pair of side-sharing ( point-sharing) solutions, these remaining solutions must be a point-sharing ( side-sharing ) pair.

Robust Face Detection via Learning Small Faces on Hard Images

1 code implementation28 Nov 2018 Zhishuai Zhang, Wei Shen, Siyuan Qiao, Yan Wang, Bo wang, Alan Yuille

In this paper, we propose that the robustness of a face detector against hard faces can be improved by learning small faces on hard images.

Face Detection

Image Captioning based on Deep Reinforcement Learning

no code implementations13 Sep 2018 Haichao Shi, Peng Li, Bo wang, Zhenyu Wang

However, in this paper, we propose a novel architecture for image captioning with deep reinforcement learning to optimize image captioning tasks.

Image Captioning Policy Gradient Methods +2

Network Enhancement: a general method to denoise weighted biological networks

no code implementations9 May 2018 Bo Wang, Armin Pourshafeie, Marinka Zitnik, Junjie Zhu, Carlos D. Bustamante, Serafim Batzoglou, Jure Leskovec

Networks are ubiquitous in biology where they encode connectivity patterns at all scales of organization, from molecular to the biome.

Denoising

Deep Co-Training for Semi-Supervised Image Recognition

1 code implementation ECCV 2018 Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo wang, Alan Yuille

We present Deep Co-Training, a deep learning based method inspired by the Co-Training framework.

Test

Single-Shot Object Detection with Enriched Semantics

no code implementations CVPR 2018 Zhishuai Zhang, Siyuan Qiao, Cihang Xie, Wei Shen, Bo wang, Alan L. Yuille

Our motivation is to enrich the semantics of object detection features within a typical deep detector, by a semantic segmentation branch and a global activation module.

Object object-detection +4