no code implementations • WAT 2022 • Yilun Liu, Zhen Zhang, Shimin Tao, Junhui Li, Hao Yang
In this paper we describe our submission to the shared tasks of the 9th Workshop on Asian Translation (WAT 2022) on NICT–SAP under the team name ”HwTscSU”.
1 code implementation • Findings (NAACL) 2022 • Zhen Zhang, Wei Zhu, Jinfan Zhang, Peng Wang, Rize Jin, Tae-Sun Chung
In this work, we propose Patient and Confident Early Exiting BERT (PCEE-BERT), an off-the-shelf sample-dependent early exiting method that can work with different PLMs and can also work along with popular model compression methods.
no code implementations • 28 Nov 2023 • Yichao Cai, Yuhang Liu, Zhen Zhang, Javen Qinfeng Shi
By changing the style part of the text data, we empower the text encoder to emphasize latent content variables, ultimately enhancing the robustness of vision-language models.
no code implementations • 24 Oct 2023 • Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton Van Den Hengel, Kun Zhang, Javen Qinfeng Shi
However, this progress rests on the assumption that the causal relationships among latent causal variables adhere strictly to linear Gaussian models.
no code implementations • 13 Oct 2023 • Zhen Zhang, Anran Lin, Chun Wai Wong, Xiangyu Chu, Qi Dou, K. W. Samuel Au
This paper proposes an interactive navigation framework by using large language and vision-language models, allowing robots to navigate in environments with traversable obstacles.
no code implementations • 2 Oct 2023 • Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He
While numerous public blockchain datasets are available, their utility is constrained by a singular focus on blockchain data.
no code implementations • 15 Sep 2023 • Zhengliang Shi, Weiwei Sun, Shuo Zhang, Zhen Zhang, Pengjie Ren, Zhaochun Ren
To this end, we propose the Reference-Assisted Dialogue Evaluation (RADE) approach under the multi-task learning framework, which leverages the pre-created utterance as reference other than the gold response to relief the one-to-many problem.
1 code implementation • 15 Sep 2023 • Insu Jang, Zhenning Yang, Zhen Zhang, Xin Jin, Mosharaf Chowdhury
Oobleck enables resilient distributed training of large DNN models with guaranteed fault tolerance.
1 code implementation • 13 Sep 2023 • Yining Luo, Yingfa Chen, Zhen Zhang
Compared to existing datasets, the advantages of CFDBench are (1) comprehensive.
no code implementations • 30 Aug 2023 • Zhen Zhang, Hongrui Sun, Hui Sun
Capacity attenuation is one of the most intractable issues in the current of application of the cells.
no code implementations • NeurIPS 2020 • Zhen Zhang, Mohammed Haroon Dupty, Fan Wu, Javen Qinfeng Shi, Wee Sun Lee
In recent years, we have witnessed a surge of Graph Neural Networks (GNNs), most of which can learn powerful representations in an end-to-end fashion with great success in many real-world applications.
no code implementations • 16 Jul 2023 • Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis
Specifically, we integrate physics informed neural networks (PINNs) and symbolic regression to discover a reaction-diffusion type partial differential equation for tau protein misfolding and spreading.
1 code implementation • 14 Jul 2023 • Zhen Zhang, Guanhua Zhang, Bairu Hou, Wenqi Fan, Qing Li, Sijia Liu, Yang Zhang, Shiyu Chang
This largely falls into the study of certified robust LLMs, i. e., all predictions of LLM are certified to be correct in a local region around the input.
1 code implementation • 5 Jul 2023 • Shengding Hu, Ning Ding, Weilin Zhao, Xingtai Lv, Zhen Zhang, Zhiyuan Liu, Maosong Sun
The scale of large pre-trained models (PTMs) poses significant challenges in adapting to downstream tasks due to the high optimization overhead and storage costs associated with full-parameter fine-tuning.
no code implementations • 5 Jun 2023 • Mengting Hu, Zhen Zhang, Shiwan Zhao, Minlie Huang, Bingzhe Wu
Therefore, in this survey, we provide a comprehensive review of uncertainty-relevant works in the NLP field.
no code implementations • 3 Jun 2023 • Zibing Shen, Jianhua Zhang, Li Yu, Yuxiang Zhang, Zhen Zhang, Xidong Hu
A common and accurate dataset is essential for the research of AI communication.
1 code implementation • 1 Jun 2023 • Mengting Hu, Yinhao Bai, Yike Wu, Zhen Zhang, Liqi Zhang, Hang Gao, Shiwan Zhao, Minlie Huang
We further propose marginalized unlikelihood learning to suppress the uncertainty-aware mistake tokens.
1 code implementation • 29 May 2023 • Zhen Zhang, Mengting Hu, Shiwan Zhao, Minlie Huang, Haotian Wang, Lemao Liu, Zhirui Zhang, Zhe Liu, Bingzhe Wu
Most named entity recognition (NER) systems focus on improving model performance, ignoring the need to quantify model uncertainty, which is critical to the reliability of NER systems in open environments.
1 code implementation • 18 May 2023 • Xuran Li, Peng Wu, Kaixiang Dong, Zhen Zhang, Yanting Chen
This matrix categorizes predictions as true fair, true biased, false fair, and false biased, and the perturbations guided by it can produce a dual impact on instances and their similar counterparts to either undermine prediction accuracy (robustness) or cause biased predictions (individual fairness).
1 code implementation • 2 May 2023 • Zhen Zhang, Jialu Wang, Xin Eric Wang
Extensive experiments on XTD and Multi30K datasets, covering 11 languages under zero-shot, few-shot, and full-dataset learning scenarios, show that our framework significantly reduces the multilingual disparities among languages and improves cross-lingual transfer results, especially in low-resource scenarios, while only keeping and fine-tuning an extremely small number of parameters compared to the full model (e. g., Our framework only requires 0. 16\% additional parameters of a full-model for each language in the few-shot learning scenario).
3 code implementations • 17 Apr 2023 • Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Zhiyuan Liu, Maosong Sun
Considering the lack of a systematic tool learning evaluation in prior works, we experiment with 18 representative tools and show the potential of current foundation models in skillfully utilizing tools.
no code implementations • 13 Apr 2023 • Yue Cao, Zhen Zhang
By means of the ESO feedback, the plant model is kept as nominal, and hence the structural robustness is achieved for the time-varying internal model.
1 code implementation • 29 Mar 2023 • Sihao Hu, Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He, Ling Liu
As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these malicious activities to protect susceptible users from being victimized.
no code implementations • 25 Mar 2023 • Zhen Zhang, Masaki Takeda, Makoto Iwata
Neural decoding of visual object classification via functional magnetic resonance imaging (fMRI) data is challenging and is vital to understand underlying brain mechanisms.
no code implementations • 16 Feb 2023 • Hongzheng Chen, Cody Hao Yu, Shuai Zheng, Zhen Zhang, Zhiru Zhang, Yida Wang
Specifically, the schedule works on a PyTorch model and uses a set of schedule primitives to convert the model for common model training optimizations such as high-performance kernels, effective 3D parallelism, and efficient activation checkpointing.
no code implementations • 28 Dec 2022 • Yang Zhou, Fuzeng Li, Xianfeng Xu, Zhen Zhang, Alexandre Ravey, Marie-Cécile Péra, Ruiqing Ma
Fuel cell electric vehicles have earned substantial attentions in recent decades due to their high-efficiency and zero-emission features, while the high operating costs remain the major barrier towards their large-scale commercialization.
1 code implementation • NIPS 2022 • Shengding Hu, Zhen Zhang, Ning Ding, Yadao Wang, Yasheng Wang, Zhiyuan Liu, Maosong Sun
Generally, DT methods exquisitely design delta modules (DT modules) which could be applied to arbitrary fine-grained positions inside PTMs.
no code implementations • 26 Oct 2022 • Hanshan Zhang, Zhen Zhang, Hongfei Jiang, Yang song
Active learning for sentence understanding attempts to reduce the annotation cost by identifying the most informative examples.
no code implementations • 17 Sep 2022 • Yutong Sun, Jianhua Zhang, Li Yu, Zhen Zhang, Ping Zhang
Inspired by task-oriented semantic communication and machine learning (ML) powered environment-channel mapping methods, this work aims to provide a new view of the environment from the semantic level, which defines the propagation environment semantics (PES) as a limited set of propagation environment semantic symbols (PESS) for diverse application tasks.
1 code implementation • 30 Aug 2022 • Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan M Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi
Recovering underlying Directed Acyclic Graph (DAG) structures from observational data is highly challenging due to the combinatorial nature of the DAG-constrained optimization problem.
no code implementations • 30 Aug 2022 • Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton Van Den Hengel, Kun Zhang, Javen Qinfeng Shi
The task of causal representation learning aims to uncover latent higher-level causal representations that affect lower-level observations.
no code implementations • 30 Aug 2022 • Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Kun Zhang, Javen Qinfeng Shi
This motivates us to propose a novel method for MSDA, which learns the invariant label distribution conditional on the latent content variable, instead of learning invariant representations.
no code implementations • 15 Jun 2022 • Shengding Hu, Zhen Zhang, Ning Ding, Yadao Wang, Yasheng Wang, Zhiyuan Liu, Maosong Sun
The searched structures preserve more than 99\% fine-tuning performance with 0. 01\% trainable parameters.
no code implementations • 1 Jun 2022 • Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang
Accordingly, we for the first time propose to model the biased credit scoring data with Multi-Task Learning (MTL).
no code implementations • 25 May 2022 • Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park
The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).
no code implementations • 23 May 2022 • Youjun Xu, Jinchuan Xiao, Chia-Han Chou, Jianhang Zhang, Jintao Zhu, Qiwan Hu, Hemin Li, Ningsheng Han, Bingyu Liu, Shuaipeng Zhang, Jinyu Han, Zhen Zhang, Shuhao Zhang, Weilin Zhang, Luhua Lai, Jianfeng Pei
Due to a backlog of decades and an increasing amount of these printed literature, there is a high demand for the translation of printed depictions into machine-readable formats, which is known as Optical Chemical Structure Recognition (OCSR).
no code implementations • 25 Apr 2022 • Zhen Zhang, Yuxiang Zhang, Jianhua Zhang, Feifei Gao
In this paper, a time-varying channel prediction method based on conditional generative adversarial network (CPcGAN) is proposed for time division duplexing/frequency division duplexing (TDD/FDD) systems.
1 code implementation • 21 Apr 2022 • Sihao Hu, Zhen Zhang, Shengliang Lu, Bingsheng He, Zhao Li
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susceptible investors.
no code implementations • 23 Mar 2022 • Yue Cao, Zhen Zhang
The proposed TV-IMCC is twofold, including an extended position domain framework with master-slave structures for contour regulation, and a time-varying internal model principle-based controller for each axial tracking precision improvement.
2 code implementations • 3 Feb 2022 • Mitchell Daneker, Zhen Zhang, George Em Karniadakis, Lu Lu
The dynamics of systems biological processes are usually modeled by a system of ordinary differential equations (ODEs) with many unknown parameters that need to be inferred from noisy and sparse measurements.
1 code implementation • 14 Jan 2022 • Tingwei Meng, Zhen Zhang, Jérôme Darbon, George Em Karniadakis
Solving high-dimensional optimal control problems in real-time is an important but challenging problem, with applications to multi-agent path planning problems, which have drawn increased attention given the growing popularity of drones in recent years.
no code implementations • 10 Jan 2022 • Lei LI, Fuping Wu, Sihan Wang, Xinzhe Luo, Carlos Martin-Isla, Shuwei Zhai, Jianpeng Zhang, Yanfei Liu7, Zhen Zhang, Markus J. Ankenbrand, Haochuan Jiang, Xiaoran Zhang, Linhong Wang, Tewodros Weldebirhan Arega, Elif Altunok, Zhou Zhao, Feiyan Li, Jun Ma, Xiaoping Yang, Elodie Puybareau, Ilkay Oksuz, Stephanie Bricq, Weisheng Li, Kumaradevan Punithakumar, Sotirios A. Tsaftaris, Laura M. Schreiber, Mingjing Yang, Guocai Liu, Yong Xia, Guotai Wang, Sergio Escalera, Xiahai Zhuang
Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment.
no code implementations • 31 Aug 2021 • Zhen Zhang, Yeonjong Shin, George Em Karniadakis
We propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism.
1 code implementation • 30 Jul 2021 • Yun Yue, Yongchao Liu, Suo Tong, Minghao Li, Zhen Zhang, Chunyang Wen, Huanjun Bao, Lihong Gu, Jinjie Gu, Yixiang Mu
We develop a novel framework that adds the regularizers of the sparse group lasso to a family of adaptive optimizers in deep learning, such as Momentum, Adagrad, Adam, AMSGrad, AdaHessian, and create a new class of optimizers, which are named Group Momentum, Group Adagrad, Group Adam, Group AMSGrad and Group AdaHessian, etc., accordingly.
no code implementations • 14 Jul 2021 • Ning Ma, Jiajun Bu, Zhen Zhang, Sheng Zhou
Present domain adaptation methods usually perform explicit representation alignment by simultaneously accessing the source data and target data.
no code implementations • 14 Jul 2021 • Ning Ma, Jiajun Bu, Lixian Lu, Jun Wen, Zhen Zhang, Sheng Zhou, Xifeng Yan
Domain Adaptation has been widely used to deal with the distribution shift in vision, language, multimedia etc.
no code implementations • 22 Mar 2021 • Lin Pan, Yaoyong Zheng, Liqin Huang, Liuqing Chen, Zhen Zhang, Rongda Fu, Bin Zheng, Shaohua Zheng
We propose a novel method for automatic separation of pulmonary arteries and veins from chest CT images.
no code implementations • 1 Jan 2021 • Yun Yue, Suo Tong, Zhen Zhang, Yongchao Liu, Chunyang Wen, Huanjun Bao, Jinjie Gu, Yixiang Mu
We develop a novel framework that adds the regularizers to a family of adaptive optimizers in deep learning, such as MOMENTUM, ADAGRAD, ADAM, AMSGRAD, ADAHESSIAN, and create a new class of optimizers, which are named GROUP MOMENTUM, GROUP ADAGRAD, GROUP ADAM, GROUP AMSGRAD and GROUP ADAHESSIAN, etc., accordingly.
no code implementations • 23 Dec 2020 • Zhen Zhang, Dave Cliff
We demonstrate that the new imbalance-sensitive trader-agents introduced here do exhibit market impact effects, and hence are better-suited to operating in markets where impact is a factor of concern or interest, but do not suffer the weaknesses of the methods used by Church & Cliff.
1 code implementation • 5 Dec 2020 • Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis, George Em Karniadakis
We propose the Poisson neural networks (PNNs) to learn Poisson systems and trajectories of autonomous systems from data.
no code implementations • 24 Nov 2020 • Zhao Li, Yixin Liu, Zhen Zhang, Shirui Pan, Jianliang Gao, Jiajun Bu
To overcome these limitations, we introduce a novel framework for graph semi-supervised learning termed as Cyclic Label Propagation (CycProp for abbreviation), which integrates GNNs into the process of label propagation in a cyclic and mutually reinforcing manner to exploit the advantages of both GNNs and LPA.
no code implementations • 13 Nov 2020 • Jun Zhang, Yao-Kun Lei, Zhen Zhang, Xu Han, Maodong Li, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao
Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL$^\ddag$) to automatically unravel chemical reaction mechanisms.
1 code implementation • 1 Nov 2020 • Licheng Wen, Zhen Zhang, Zhe Chen, Xiangrui Zhao, Yong liu
In this paper, we give a mathematical formalization of Multi-Agent Path Finding for Car-Like robots (CL-MAPF) problem.
Robotics Multiagent Systems
no code implementations • 29 Oct 2020 • Chenyu Liu, Wangbin Ding, Lei LI, Zhen Zhang, Chenhao Pei, Liqin Huang, Xiahai Zhuang
Considering that multi-modal MR images can reflect different tumor biological properties, we develop a novel multi-modal tumor segmentation network (MMTSN) to robustly segment brain tumors based on multi-modal MR images.
no code implementations • 15 Oct 2020 • Zhen Zhang, Jing-Yang You, Xing-Yu Ma, Bo Gu, Gang Su
For the bilayer compound Co6Sn5Se4, it becomes a half-metal, with a relatively flat plateau in its anomalous Hall conductivity corresponding to |C| = 3 near the Fermi level.
Materials Science
1 code implementation • 13 Aug 2020 • Zhen Zhang, Chenyu Liu, Wangbin Ding, Sihan Wang, Chenhao Pei, Mingjing Yang, Liqin Huang
The PRSN is designed to segment pathological region based on the result of ASSN, in which a fusion block based on channel attention is proposed to better aggregate multi-modality information from multi-modality CMR images.
no code implementations • 4 Aug 2020 • Yuzhu Wu, Zhen Zhang, Gang Kou, Hengjie Zhang, Xiangrui Chao, Cong-Cong Li, Yucheng Dong, Francisco Herrera
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making.
no code implementations • 13 Jul 2020 • Wei Shao, Sichen Zhao, Zhen Zhang, Shiyu Wang, Mohammad Saiedur Rahaman, Andy Song, Flora Dilys Salim
We quantify the strength of our proposed framework in different cases and compare it to the existing data-driven approaches.
1 code implementation • 17 Jun 2020 • Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
As such, we advocate that the real challenge of distributed training is for the network community to develop high-performance network transport to fully utilize the network capacity and achieve linear scale-out.
no code implementations • 29 May 2020 • Lijie Zhao, Haiyun Xia, Yihua Hu, Tengfei Wu, Zhen Zhang, Jibo Han, Yunbin Wu, Tiancheng Luo
After that, the frequency variation of the microwave pulse is uploaded to the first order sidebands.
no code implementations • 25 Apr 2020 • Jun Zhang, Yao-Kun Lei, Zhen Zhang, Junhan Chang, Maodong Li, Xu Han, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao
Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems.
no code implementations • 18 Mar 2020 • Ning Ma, Jiajun Bu, Jieyu Yang, Zhen Zhang, Chengwei Yao, Zhi Yu, Sheng Zhou, Xifeng Yan
The shared sub-structures between training classes and test classes are essential in few-shot graph classification.
no code implementations • 29 Feb 2020 • Xuan Su, Wee Sun Lee, Zhen Zhang
We propose a new sampling-based approach for approximate inference in filtering problems.
1 code implementation • 11 Jan 2020 • Pengzhan Jin, Zhen Zhang, Aiqing Zhu, Yifa Tang, George Em. Karniadakis
We propose new symplectic networks (SympNets) for identifying Hamiltonian systems from data based on a composition of linear, activation and gradient modules.
no code implementations • 25 Nov 2019 • Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu Aggarwal
In particular, RGE is shown to achieve \emph{(quasi-)linear scalability} with respect to the number and the size of the graphs.
1 code implementation • NeurIPS 2019 • Zhen Zhang, Yijian Xiang, Lingfei Wu, Bing Xue, Arye Nehorai
Graph matching plays a central role in such fields as computer vision, pattern recognition, and bioinformatics.
no code implementations • 22 Nov 2019 • Mohammed Haroon Dupty, Zhen Zhang, Wee Sun Lee
We address the problem of Visual Relationship Detection (VRD) which aims to describe the relationships between pairs of objects in the form of triplets of (subject, predicate, object).
3 code implementations • 14 Nov 2019 • Zhen Zhang, Jiajun Bu, Martin Ester, Jianfeng Zhang, Chengwei Yao, Zhi Yu, Can Wang
HGP-SL incorporates graph pooling and structure learning into a unified module to generate hierarchical representations of graphs.
Ranked #1 on
Graph Classification
on PROTEINS
no code implementations • ICCV 2019 • Zhen Zhang, Wee Sun Lee
Rich local representation is a key part of efficient feature matching methods.
no code implementations • 7 Jun 2019 • Jun Zhang, Yao-Kun Lei, Xing Che, Zhen Zhang, Yi Isaac Yang, Yi Qin Gao
In this paper we first analyzed the inductive bias underlying the data scattered across complex free energy landscapes (FEL), and exploited it to train deep neural networks which yield reduced and clustered representation for the FEL.
1 code implementation • 3 Jun 2019 • Zhen Zhang, Fan Wu, Wee Sun Lee
Most of the successful deep neural network architectures are structured, often consisting of elements like convolutional neural networks and gated recurrent neural networks.
1 code implementation • 18 Feb 2019 • Zhen Zhang, Dong-Bo Zhang, Tao Sun, Renata Wentzcovitch
We here introduce a Fortran code that computes anharmonic free energy of solids from first-principles based on our phonon quasiparticle approach.
Materials Science
no code implementations • NeurIPS 2018 • Zhen Zhang, Mianzhi Wang, Yijian Xiang, Yan Huang, Arye Nehorai
Graph-structured data arise in wide applications, such as computer vision, bioinformatics, and social networks.
no code implementations • CVPR 2018 • Zhen Zhang, Mianzhi Wang, Yan Huang, Arye Nehorai
Domain shift, which occurs when there is a mismatch between the distributions of training (source) and testing (target) datasets, usually results in poor performance of the trained model on the target domain.
1 code implementation • CVPR 2018 • Chen Li, Zhen Zhang, Wee Sun Lee, Gim Hee Lee
Human motion modeling is a classic problem in computer vision and graphics.
no code implementations • 14 Apr 2018 • Shiyong Ma, Zhen Zhang
We developed OmicsMapNet approach to take advantage of existing deep leaning frameworks to analyze high-dimensional omics data as 2-dimensional images.
1 code implementation • 10 Apr 2018 • Dong Gong, Zhen Zhang, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Yanning Zhang
Extensive experiments on synthetic benchmarks and challenging real-world images demonstrate that the proposed deep optimization method is effective and robust to produce favorable results as well as practical for real-world image deblurring applications.
no code implementations • ICCV 2017 • Jiandong Tian, Zachary Murez, Tong Cui, Zhen Zhang, David Kriegman, Ravi Ramamoorthi
First, we present a new single image restoration algorithm which removes backscatter and attenuation from images better than existing methods, and apply it to each view in the light field.
no code implementations • CVPR 2016 • Seyed Hamid Rezatofighi, Anton Milan, Zhen Zhang, Qinfeng Shi, Anthony Dick, Ian Reid
Matching between two sets of objects is typically approached by finding the object pairs that collectively maximize the joint matching score.
no code implementations • CVPR 2016 • Zhen Zhang, Qinfeng Shi, Julian McAuley, Wei Wei, Yanning Zhang, Anton Van Den Hengel
Feature matching is a key problem in computer vision and pattern recognition.
no code implementations • ICCV 2015 • Seyed Hamid Rezatofighi, Anton Milan, Zhen Zhang, Qinfeng Shi, Anthony Dick, Ian Reid
In this paper, we revisit the joint probabilistic data association (JPDA) technique and propose a novel solution based on recent developments in finding the m-best solutions to an integer linear program.
no code implementations • CVPR 2015 • Mingkui Tan, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Junbin Gao, Fuyuan Hu, Zhen Zhang
Exploiting label dependency for multi-label image classification can significantly improve classification performance.
no code implementations • 4 Apr 2015 • Zhen Zhang, Chonghui Guo, Luis Martínez
Linguistic large-scale group decision making (LGDM) problems are more and more common nowadays.
no code implementations • 17 Dec 2013 • Zhen Zhang, Qinfeng Shi, Yanning Zhang, Chunhua Shen, Anton Van Den Hengel
We show that using Marginal Polytope Diagrams allows the number of constraints to be reduced without loosening the LP relaxations.
no code implementations • 25 Oct 2013 • Niya Wang, Eric P. Hoffman, Robert Clarke, Zhen Zhang, David M. Herrington, Ie-Ming Shih, Douglas A. Levine, Guoqiang Yu, Jianhua Xuan, Yue Wang
Tissue heterogeneity is a major confounding factor in studying individual populations that cannot be resolved directly by global profiling.