Search Results for author: Yuan Gao

Found 111 papers, 42 papers with code

Deep Gate Recurrent Neural Network

no code implementations11 Apr 2016 Yuan Gao, Dorota Glowacka

This paper introduces two recurrent neural network structures called Simple Gated Unit (SGU) and Deep Simple Gated Unit (DSGU), which are general structures for learning long term dependencies.

Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images

no code implementations CVPR 2017 Yuan Gao, Alan L. Yuille

By assuming an orthographic projection model, this paper addresses the estimation of 3D structures and camera projection using symmetry and/or Manhattan structure cues, which occur when the input is single- or multiple-image from the same category, e. g., multiple different cars.

Semi-Supervised Sparse Representation Based Classification for Face Recognition with Insufficient Labeled Samples

no code implementations12 Sep 2016 Yuan Gao, Jiayi Ma, Alan L. Yuille

This is based on recent work on sparsity where faces are represented in terms of two dictionaries: a gallery dictionary consisting of one or more examples of each person, and a variation dictionary representing linear nuisance variables (e. g., different lighting conditions, different glasses).

Face Recognition General Classification +1

Symmetric Non-Rigid Structure from Motion for Category-Specific Object Structure Estimation

no code implementations22 Sep 2016 Yuan Gao, Alan Yuille

This paper addresses the estimation of 3D structures of symmetric objects from multiple images of the same object category, e. g. different cars, seen from various viewpoints.

Convex Geometry of the Generalized Matrix-Fractional Function

no code implementations4 Mar 2017 James V. Burke, Yuan Gao, Tim Hoheisel

Generalized matrix-fractional (GMF) functions are a class of matrix support functions introduced by Burke and Hoheisel as a tool for unifying a range of seemingly divergent matrix optimization problems associated with inverse problems, regularization and learning.

Spoken English Intelligibility Remediation with PocketSphinx Alignment and Feature Extraction Improves Substantially over the State of the Art

1 code implementation6 Sep 2017 Yuan Gao, Brij Mohan Lal Srivastava, James Salsman

We use automatic speech recognition to assess spoken English learner pronunciation based on the authentic intelligibility of the learners' spoken responses determined from support vector machine (SVM) classifier or deep learning neural network model predictions of transcription correctness.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Multi-Glimpse LSTM with Color-Depth Feature Fusion for Human Detection

no code implementations3 Nov 2017 Hengduo Li, Jun Liu, Guyue Zhang, Yuan Gao, Yirui Wu

In this paper, we propose a new Multi-Glimpse LSTM (MG-LSTM) network, in which multi-scale contextual information is sequentially integrated to promote the human detection performance.

Human Detection

NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction

1 code implementation CVPR 2019 Yuan Gao, Jiayi Ma, Mingbo Zhao, Wei Liu, Alan L. Yuille

In this paper, we propose a novel Convolutional Neural Network (CNN) structure for general-purpose multi-task learning (MTL), which enables automatic feature fusing at every layer from different tasks.

Multi-Task Learning Semantic Segmentation

Unity: A General Platform for Intelligent Agents

56 code implementations7 Sep 2018 Arthur Juliani, Vincent-Pierre Berges, Ervin Teng, Andrew Cohen, Jonathan Harper, Chris Elion, Chris Goy, Yuan Gao, Hunter Henry, Marwan Mattar, Danny Lange

Recent advances in artificial intelligence have been driven by the presence of increasingly realistic and complex simulated environments.

Unity

Learning Socially Appropriate Robot Approaching Behavior Toward Groups using Deep Reinforcement Learning

1 code implementation16 Oct 2018 Yuan Gao, Fangkai Yang, Martin Frisk, Daniel Hernandez, Christopher Peters, Ginevra Castellano

Deep reinforcement learning has recently been widely applied in robotics to study tasks such as locomotion and grasping, but its application to social human-robot interaction (HRI) remains a challenge.

reinforcement-learning Reinforcement Learning (RL)

Deep Generative Learning via Variational Gradient Flow

1 code implementation24 Jan 2019 Yuan Gao, Yuling Jiao, Yang Wang, Yao Wang, Can Yang, Shunkang Zhang

We propose a general framework to learn deep generative models via \textbf{V}ariational \textbf{Gr}adient Fl\textbf{ow} (VGrow) on probability spaces.

Binary Classification

Wasserstein-Wasserstein Auto-Encoders

no code implementations25 Feb 2019 Shunkang Zhang, Yuan Gao, Yuling Jiao, Jin Liu, Yang Wang, Can Yang

To address the challenges in learning deep generative models (e. g., the blurriness of variational auto-encoder and the instability of training generative adversarial networks, we propose a novel deep generative model, named Wasserstein-Wasserstein auto-encoders (WWAE).

Increasing Iterate Averaging for Solving Saddle-Point Problems

no code implementations26 Mar 2019 Yuan Gao, Christian Kroer, Donald Goldfarb

In particular, the increasing averages consistently outperform the uniform averages in all test problems by orders of magnitude.

Image Denoising

Intra-Ensemble in Neural Networks

no code implementations9 Apr 2019 Yuan Gao, Zixiang Cai, Lei Yu

In this work, we propose Intra-Ensemble, an end-to-end ensemble strategy with stochastic channel recombination operations to train several sub-networks simultaneously within one neural network.

Fast Adaptation with Meta-Reinforcement Learning for Trust Modelling in Human-Robot Interaction

no code implementations12 Aug 2019 Yuan Gao, Elena Sibirtseva, Ginevra Castellano, Danica Kragic

In socially assistive robotics, an important research area is the development of adaptation techniques and their effect on human-robot interaction.

Meta-Learning Meta Reinforcement Learning +3

Skew-Explore: Learn faster in continuous spaces with sparse rewards

no code implementations25 Sep 2019 Xi Chen, Yuan Gao, Ali Ghadirzadeh, Marten Bjorkman, Ginevra Castellano, Patric Jensfelt

In this work, we introduce an exploration approach based on maximizing the entropy of the visited states while learning a goal-conditioned policy.

Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

3 code implementations9 Nov 2019 Iddo Drori, Darshan Thaker, Arjun Srivatsa, Daniel Jeong, Yueqi Wang, Linyong Nan, Fan Wu, Dimitri Leggas, Jinhao Lei, Weiyi Lu, Weilong Fu, Yuan Gao, Sashank Karri, Anand Kannan, Antonio Moretti, Mohammed AlQuraishi, Chen Keasar, Itsik Pe'er

Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.

Multiple Sequence Alignment Protein Structure Prediction

Automated Testing for Deep Learning Systems with Differential Behavior Criteria

no code implementations31 Dec 2019 Yuan Gao, Yiqiang Han

By observing differential behaviors from three pre-trained models during each testing iteration, the input image that triggered erroneous feedback was registered as a corner-case.

Learning Implicit Generative Models with Theoretical Guarantees

no code implementations7 Feb 2020 Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu

We then solve the McKean-Vlasov equation numerically using the forward Euler iteration, where the forward Euler map depends on the density ratio (density difference) between the distribution at current iteration and the underlying target distribution.

Application of Deep Q-Network in Portfolio Management

no code implementations13 Mar 2020 Ziming Gao, Yuan Gao, Yi Hu, Zhengyong Jiang, Jionglong Su

This paper will introduce a strategy based on the classic Deep Reinforcement Learning algorithm, Deep Q-Network, for portfolio management in stock market.

Face Recognition Management +2

DRST: Deep Residual Shearlet Transform for Densely Sampled Light Field Reconstruction

no code implementations19 Mar 2020 Yuan Gao, Robert Bregovic, Reinhard Koch, Atanas Gotchev

Specifically, for an input sparsely-sampled EPI, DRST employs a deep fully Convolutional Neural Network (CNN) to predict the residuals of the shearlet coefficients in shearlet domain in order to reconstruct a densely-sampled EPI in image domain.

Self-Supervised Light Field Reconstruction Using Shearlet Transform and Cycle Consistency

no code implementations20 Mar 2020 Yuan Gao, Robert Bregovic, Atanas Gotchev

Specifically, CycleST is composed of an encoder-decoder network and a residual learning strategy that restore the shearlet coefficients of densely-sampled EPIs using EPI reconstruction and cycle consistency losses.

Signal Processing Multimedia Image and Video Processing

Stochastic Flows and Geometric Optimization on the Orthogonal Group

no code implementations ICML 2020 Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani

We present a new class of stochastic, geometrically-driven optimization algorithms on the orthogonal group $O(d)$ and naturally reductive homogeneous manifolds obtained from the action of the rotation group $SO(d)$.

Metric Learning Stochastic Optimization

Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification from CT Images

no code implementations14 Apr 2020 Shaoping Hu, Yuan Gao, Zhangming Niu, Yinghui Jiang, Lao Li, Xianglu Xiao, Minhao Wang, Evandro Fei Fang, Wade Menpes-Smith, Jun Xia, Hui Ye, Guang Yang

An outbreak of a novel coronavirus disease (i. e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world.

General Classification Respiratory Failure

Data-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions

no code implementations22 May 2020 Yuan Gao, Jian-Guo Liu, Nan Wu

To construct an efficient and stable approximation for the Langevin dynamics on $\mathcal{N}$, we leverage the corresponding Fokker-Planck equation on the manifold $\mathcal{N}$ in terms of the reaction coordinates $\mathsf{y}$.

An Improved Analysis of Stochastic Gradient Descent with Momentum

1 code implementation NeurIPS 2020 Yanli Liu, Yuan Gao, Wotao Yin

Furthermore, the role of dynamic parameters has not been addressed.

Optimization and Control

Graph-PCNN: Two Stage Human Pose Estimation with Graph Pose Refinement

no code implementations ECCV 2020 Jian Wang, Xiang Long, Yuan Gao, Errui Ding, Shilei Wen

In the first stage, heatmap regression network is applied to obtain a rough localization result, and a set of proposal keypoints, called guided points, are sampled.

Pose Estimation regression +1

PP-YOLO: An Effective and Efficient Implementation of Object Detector

5 code implementations23 Jul 2020 Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan Gao, Hui Shen, Jianguo Ren, Shumin Han, Errui Ding, Shilei Wen

We mainly try to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to achieve the goal of improving the accuracy of detector as much as possible while ensuring that the speed is almost unchanged.

Ranked #134 on Object Detection on COCO test-dev (using extra training data)

Object object-detection +1

CAD-PU: A Curvature-Adaptive Deep Learning Solution for Point Set Upsampling

1 code implementation10 Sep 2020 Jiehong Lin, Xian Shi, Yuan Gao, Ke Chen, Kui Jia

Point set is arguably the most direct approximation of an object or scene surface, yet its practical acquisition often suffers from the shortcoming of being noisy, sparse, and possibly incomplete, which restricts its use for a high-quality surface recovery.

Point Set Upsampling

Recognizing Micro-Expression in Video Clip with Adaptive Key-Frame Mining

1 code implementation19 Sep 2020 Min Peng, Chongyang Wang, Yuan Gao, Tao Bi, Tong Chen, Yu Shi, Xiang-Dong Zhou

As a spontaneous expression of emotion on face, micro-expression reveals the underlying emotion that cannot be controlled by human.

Partial FC: Training 10 Million Identities on a Single Machine

7 code implementations11 Oct 2020 Xiang An, Xuhan Zhu, Yang Xiao, Lan Wu, Ming Zhang, Yuan Gao, Bin Qin, Debing Zhang, Ying Fu

The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.

Face Identification Face Recognition +2

Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data

1 code implementation3 Nov 2020 Chongyang Wang, Yuan Gao, Akhil Mathur, Amanda C. De C. Williams, Nicholas D. Lane, Nadia Bianchi-Berthouze

Protective behavior exhibited by people with chronic pain (CP) during physical activities is the key to understanding their physical and emotional states.

Human Activity Recognition Management

Generative Learning With Euler Particle Transport

no code implementations11 Dec 2020 Yuan Gao, Jian Huang, Yuling Jiao, Jin Liu, Xiliang Lu, Zhijian Yang

The key task in training is the estimation of the density ratios or differences that determine the residual maps.

Exploiting Learnable Joint Groups for Hand Pose Estimation

1 code implementation17 Dec 2020 Moran Li, Yuan Gao, Nong Sang

This is different from the previous methods where all the joints are considered holistically and share the same feature.

Hand Pose Estimation Multi-Task Learning

Temporal Cue Guided Video Highlight Detection With Low-Rank Audio-Visual Fusion

no code implementations ICCV 2021 Qinghao Ye, Xiyue Shen, Yuan Gao, ZiRui Wang, Qi Bi, Ping Li, Guang Yang

Video highlight detection plays an increasingly important role in social media content filtering, however, it remains highly challenging to develop automated video highlight detection methods because of the lack of temporal annotations (i. e., where the highlight moments are in long videos) for supervised learning.

Highlight Detection Model Optimization

Factor-augmented Smoothing Model for Functional Data

no code implementations4 Feb 2021 Yuan Gao, Han Lin Shang, Yanrong Yang

We propose modeling raw functional data as a mixture of a smooth function and a highdimensional factor component.

Methodology Statistics Theory Statistics Theory

Significant Inverse Magnetocaloric Effect induced by Quantum Criticality

no code implementations17 Feb 2021 Tao Liu, Xin-Yang Liu, Yuan Gao, Hai Jin, Jun He, Xian-Lei Sheng, Wentao Jin, Ziyu Chen, Wei Li

Strong fluctuations in the low-$T$ quantum critical regime can give rise to a large thermal entropy change and thus significant cooling effect when approaching the QCP.

Strongly Correlated Electrons

Principled Ultrasound Data Augmentation for Classification of Standard Planes

no code implementations14 Mar 2021 Lok Hin Lee, Yuan Gao, J. Alison Noble

In this paper, we present an augmentation policy search method with the goal of improving model classification performance.

Classification Data Augmentation +1

Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework

no code implementations14 Apr 2021 Yuan Gao, Jiawei Li, Maoguo Gong, Yu Xie, A. K. Qin

Since the existing naive model parameter averaging method is contradictory to the learning paradigm of neural networks, we simulate the process of human cognition and communication, and analogy multi-party learning as a many-to-one knowledge sharing problem.

Multi-Party Dual Learning

no code implementations14 Apr 2021 Maoguo Gong, Yuan Gao, Yu Xie, A. K. Qin, Ke Pan, Yew-Soon Ong

The performance of machine learning algorithms heavily relies on the availability of a large amount of training data.

BIG-bench Machine Learning Self-Learning

Boosting Light-Weight Depth Estimation Via Knowledge Distillation

2 code implementations13 May 2021 Junjie Hu, Chenyou Fan, Hualie Jiang, Xiyue Guo, Yuan Gao, Xiangyong Lu, Tin Lun Lam

However, this KD process can be challenging and insufficient due to the large model capacity gap between the teacher and the student.

Computational Efficiency Knowledge Distillation +1

1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition

no code implementations2 Jul 2021 Pengcheng Wang, Lingqiao Ji, Zhilong Ji, Yuan Gao, Xiao Liu

In this technical report, we briefly introduce the solution of our team "TAL-ai" for (Semi-) supervised Face detection in the low light condition in UG2+ Challenge in CVPR 2021.

Face Detection Image Enhancement +2

Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation

1 code implementation ICCV 2021 Yuxiang Wei, Yupeng Shi, Xiao Liu, Zhilong Ji, Yuan Gao, Zhongqin Wu, WangMeng Zuo

It simply encourages the variation of output caused by perturbations on different latent dimensions to be orthogonal, and the Jacobian with respect to the input is calculated to represent this variation.

Disentanglement Image Generation

A Dual Adversarial Calibration Framework for Automatic Fetal Brain Biometry

no code implementations28 Aug 2021 Yuan Gao, Lok Hin Lee, Richard Droste, Rachel Craik, Sridevi Beriwal, Aris Papageorghiou, Alison Noble

This paper presents a novel approach to automatic fetal brain biometry motivated by needs in low- and medium- income countries.

Unsupervised Domain Adaptation

Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth

no code implementations8 Sep 2021 Chongyang Wang, Yuan Gao, Chenyou Fan, Junjie Hu, Tin Lun Lam, Nicholas D. Lane, Nadia Bianchi-Berthouze

For such issues, we propose a novel Learning to Agreement (Learn2Agree) framework to tackle the challenge of learning from multiple annotators without objective ground truth.

Temporal Pyramid Transformer with Multimodal Interaction for Video Question Answering

1 code implementation10 Sep 2021 Min Peng, Chongyang Wang, Yuan Gao, Yu Shi, Xiang-Dong Zhou

Targeting these issues, this paper proposes a novel Temporal Pyramid Transformer (TPT) model with multimodal interaction for VideoQA.

Natural Language Understanding Question Answering +1

Relative Entropy Gradient Sampler for Unnormalized Distributions

no code implementations6 Oct 2021 Xingdong Feng, Yuan Gao, Jian Huang, Yuling Jiao, Xu Liu

We propose a relative entropy gradient sampler (REGS) for sampling from unnormalized distributions.

Abnormal Occupancy Grid Map Recognition using Attention Network

1 code implementation18 Oct 2021 Fuqin Deng, Hua Feng, Mingjian Liang, Qi Feng, Ningbo Yi, Yong Yang, Yuan Gao, Junfeng Chen, Tin Lun Lam

The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it.

ADDS: Adaptive Differentiable Sampling for Robust Multi-Party Learning

no code implementations29 Oct 2021 Maoguo Gong, Yuan Gao, Yue Wu, A. K. Qin

Inspired by the idea of dropout in neural networks, we introduce a network sampling strategy in the multi-party setting, which distributes different subnets of the central model to clients for updating, and the differentiable sampling rates allow each client to extract optimal local architecture from the supernet according to its private data distribution.

Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images

no code implementations9 Dec 2021 Qinghao Ye, Yuan Gao, Weiping Ding, Zhangming Niu, Chengjia Wang, Yinghui Jiang, Minhao Wang, Evandro Fei Fang, Wade Menpes-Smith, Jun Xia, Guang Yang

The multi-domain shift problem for the multi-center and multi-scanner studies is therefore nontrivial that is also crucial for a dependable recognition and critical for reproducible and objective diagnosis and prognosis.

Computed Tomography (CT) Weakly-supervised Learning

Semi-Supervised Video Semantic Segmentation With Inter-Frame Feature Reconstruction

1 code implementation CVPR 2022 Jiafan Zhuang, Zilei Wang, Yuan Gao

For this task, we observe that the overfitting is surprisingly severe between labeled and unlabeled frames within a training video although they are very similar in style and contents.

Segmentation Semantic Segmentation +1

Finding Dynamics Preserving Adversarial Winning Tickets

no code implementations14 Feb 2022 Xupeng Shi, Pengfei Zheng, A. Adam Ding, Yuan Gao, Weizhong Zhang

Modern deep neural networks (DNNs) are vulnerable to adversarial attacks and adversarial training has been shown to be a promising method for improving the adversarial robustness of DNNs.

Adversarial Robustness

Bidding Agent Design in the LinkedIn Ad Marketplace

no code implementations25 Feb 2022 Yuan Gao, Kaiyu Yang, Yuanlong Chen, Min Liu, Noureddine El Karoui

We establish a general optimization framework for the design of automated bidding agent in dynamic online marketplaces.

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL

1 code implementation16 Mar 2022 Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang

Offline reinforcement learning methods hold the promise of learning policies from pre-collected datasets without the need to query the environment for new transitions.

Continuous Control Offline RL +2

Rumor Detection with Self-supervised Learning on Texts and Social Graph

no code implementations19 Apr 2022 Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang

At the core is to model the rumor characteristics inherent in rich information, such as propagation patterns in social network and semantic patterns in post content, and differentiate them from the truth.

Self-Supervised Learning

Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering

1 code implementation9 May 2022 Min Peng, Chongyang Wang, Yuan Gao, Yu Shi, Xiang-Dong Zhou

With a multiscale sampling, RMI iterates the interaction of appearance-motion information at each scale and the question embeddings to build the multilevel question-guided visual representations.

Question Answering Video Question Answering +1

VesNet-RL: Simulation-based Reinforcement Learning for Real-World US Probe Navigation

1 code implementation10 May 2022 Yuan Bi, Zhongliang Jiang, Yuan Gao, Thomas Wendler, Angelos Karlas, Nassir Navab

The results demonstrate that proposed approach can effectively and accurately navigate the probe towards the longitudinal view of vessels.

Navigate reinforcement-learning +1

Learning to Coordinate for a Worker-Station Multi-robot System in Planar Coverage Tasks

no code implementations5 Aug 2022 Jingtao Tang, Yuan Gao, Tin Lun Lam

In this paper, we focus on the multi-robot coverage path planning (mCPP) problem in large-scale planar areas with random dynamic interferers in the environment, where the robots have limited resources.

Multi-agent Reinforcement Learning

Towards Autonomous Atlas-based Ultrasound Acquisitions in Presence of Articulated Motion

1 code implementation10 Aug 2022 Zhongliang Jiang, Yuan Gao, Le Xie, Nassir Navab

Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e. g. difficulty in guaranteeing intra- and inter-operator repeatability.

Progressive Self-Distillation for Ground-to-Aerial Perception Knowledge Transfer

1 code implementation29 Aug 2022 Junjie Hu, Chenyou Fan, Mete Ozay, Hua Feng, Yuan Gao, Tin Lun Lam

In this paper, we introduce the ground-to-aerial perception knowledge transfer and propose a progressive semi-supervised learning framework that enables drone perception using only labeled data of ground viewpoint and unlabeled data of flying viewpoints.

Autonomous Driving Knowledge Distillation +1

Statistical Inference for Fisher Market Equilibrium

no code implementations29 Sep 2022 Luofeng Liao, Yuan Gao, Christian Kroer

In resource allocation, it is crucial to quantify the variability of the resource received by the agents (such as blood banks and food banks) in addition to fairness and efficiency properties of the systems.

Fairness Management

1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation

1 code implementation27 Dec 2022 Zhiwei Hu, Bo Chen, Yuan Gao, Zhilong Ji, Jinfeng Bai

The task of referring video object segmentation aims to segment the object in the frames of a given video to which the referring expressions refer.

Object Referring Video Object Segmentation +2

Wormhole MAML: Meta-Learning in Glued Parameter Space

no code implementations28 Dec 2022 Chih-Jung Tracy Chang, Yuan Gao, Beicheng Lou

In this paper, we introduce a novel variation of model-agnostic meta-learning, where an extra multiplicative parameter is introduced in the inner-loop adaptation.

Classification Meta-Learning +1

D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers

no code implementations CVPR 2023 Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu

Second, the HKDL module can generate keypoint detectors in a hierarchical way, which is helpful for detecting keypoints with diverse levels of structures.

Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI

1 code implementation1 Feb 2023 Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann

Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.

Representation Learning

IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data

1 code implementation3 Feb 2023 Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann

Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.

Lesion Classification Lesion Detection

Financial Distress Prediction For Small And Medium Enterprises Using Machine Learning Techniques

no code implementations23 Feb 2023 Yuan Gao, Biao Jiang, Jietong Zhou

As a result, there is a need to develop a productive prediction model for better order execution and adaptability to different datasets.

feature selection

Modeling of Interface Loads for EOD Suit Wearers

no code implementations27 Feb 2023 Yuan Gao, Stephanie Epstein, Murat Inalpolat, Yi-Ning Wu, Yan Gu

Explosive Ordnance Disposal (EOD) suits are widely used to protect human operators to execute emergency tasks such as bomb disposal and neutralization.

SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing

1 code implementation17 Apr 2023 Yu Guo, Yuan Gao, Ryan Wen Liu, Yuxu Lu, Jingxiang Qu, Shengfeng He, Wenqi Ren

The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details.

Image Dehazing

An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis

1 code implementation3 Jul 2023 Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann

Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.

A Novel Multi-Task Model Imitating Dermatologists for Accurate Differential Diagnosis of Skin Diseases in Clinical Images

no code implementations17 Jul 2023 Yan-Jie Zhou, Wei Liu, Yuan Gao, Jing Xu, Le Lu, Yuping Duan, Hao Cheng, Na Jin, Xiaoyong Man, Shuang Zhao, Yu Wang

Skin diseases are among the most prevalent health issues, and accurate computer-aided diagnosis methods are of importance for both dermatologists and patients.

Multi-Task Learning

On the application of Large Language Models for language teaching and assessment technology

no code implementations17 Jul 2023 Andrew Caines, Luca Benedetto, Shiva Taslimipoor, Christopher Davis, Yuan Gao, Oeistein Andersen, Zheng Yuan, Mark Elliott, Russell Moore, Christopher Bryant, Marek Rei, Helen Yannakoudakis, Andrew Mullooly, Diane Nicholls, Paula Buttery

The recent release of very large language models such as PaLM and GPT-4 has made an unprecedented impact in the popular media and public consciousness, giving rise to a mixture of excitement and fear as to their capabilities and potential uses, and shining a light on natural language processing research which had not previously received so much attention.

Grammatical Error Correction Misinformation +1

Generalized Minimum Error with Fiducial Points Criterion for Robust Learning

no code implementations9 Sep 2023 Haiquan Zhao, Yuan Gao, Yingying Zhu

In this paper, a generalized minimum error with fiducial points criterion (GMEEF) is presented by adopting the Generalized Gaussian Density (GGD) function as kernel.

Acoustic echo cancellation

E3 TTS: Easy End-to-End Diffusion-based Text to Speech

no code implementations2 Nov 2023 Yuan Gao, Nobuyuki Morioka, Yu Zhang, Nanxin Chen

Instead, E3 TTS models the temporal structure of the waveform through the diffusion process.

EControl: Fast Distributed Optimization with Compression and Error Control

no code implementations6 Nov 2023 Yuan Gao, Rustem Islamov, Sebastian Stich

Error Compensation (EC) is an extremely popular mechanism to mitigate the aforementioned issues during the training of models enhanced by contractive compression operators.

Distributed Optimization

H2 suboptimal containment control of homogeneous and heterogeneous multi-agent systems

no code implementations19 Nov 2023 Yuan Gao, Junjie Jiao, Zhongkui Li, Sandra Hirche

The aim is to design a distributed protocol by dynamic output feedback that achieves state/output containment control while the associated H2 cost is smaller than an a priori given upper bound.

Gaussian Interpolation Flows

no code implementations20 Nov 2023 Yuan Gao, Jian Huang, Yuling Jiao

Gaussian denoising has emerged as a powerful principle for constructing simulation-free continuous normalizing flows for generative modeling.

Denoising

Dynamic Dense Graph Convolutional Network for Skeleton-based Human Motion Prediction

no code implementations29 Nov 2023 Xinshun Wang, Wanying Zhang, Can Wang, Yuan Gao, Mengyuan Liu

Graph Convolutional Networks (GCN) which typically follows a neural message passing framework to model dependencies among skeletal joints has achieved high success in skeleton-based human motion prediction task.

Human motion prediction motion prediction

Inferring Hybrid Neural Fluid Fields from Videos

no code implementations NeurIPS 2023 Hong-Xing Yu, Yang Zheng, Yuan Gao, Yitong Deng, Bo Zhu, Jiajun Wu

Specifically, to deal with visual ambiguities of fluid velocity, we introduce a set of physics-based losses that enforce inferring a physically plausible velocity field, which is divergence-free and drives the transport of density.

Dynamic Reconstruction Future prediction

I2V-Adapter: A General Image-to-Video Adapter for Diffusion Models

no code implementations27 Dec 2023 Xun Guo, Mingwu Zheng, Liang Hou, Yuan Gao, Yufan Deng, Pengfei Wan, Di Zhang, Yufan Liu, Weiming Hu, ZhengJun Zha, Haibin Huang, Chongyang Ma

I2V-Adapter adeptly propagates the unnoised input image to subsequent noised frames through a cross-frame attention mechanism, maintaining the identity of the input image without any changes to the pretrained T2V model.

Video Generation

MvKSR: Multi-view Knowledge-guided Scene Recovery for Hazy and Rainy Degradation

1 code implementation8 Jan 2024 Dong Yang, Wenyu Xu, Yuan Gao, Yuxu Lu, Jingming Zhang, Yu Guo

High-quality imaging is crucial for ensuring safety supervision and intelligent deployment in fields like transportation and industry.

Alleviating Structural Distribution Shift in Graph Anomaly Detection

1 code implementation25 Jan 2024 Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

Graph anomaly detection (GAD) is a challenging binary classification problem due to its different structural distribution between anomalies and normal nodes -- abnormal nodes are a minority, therefore holding high heterophily and low homophily compared to normal nodes.

Binary Classification Graph Anomaly Detection

DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation

no code implementations5 Feb 2024 Yuan Gao, Haokun Chen, Xiang Wang, Zhicai Wang, Xue Wang, Jinyang Gao, Bolin Ding

Our research demonstrates the efficacy of leveraging AIGS and the DiffsFormer architecture to mitigate data scarcity in stock forecasting tasks.

AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge Integration

1 code implementation6 Feb 2024 Yuxu Lu, Dong Yang, Yuan Gao, Ryan Wen Liu, Jun Liu, Yu Guo

Additionally, we suggest a multi-receptive field extraction module (MEM) to attenuate the loss of image texture details caused by GC nonlinear and OLS linear transformations.

Autonomous Vehicles

Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentation

no code implementations26 Feb 2024 Yu Ming, Zihao Wu, Jie Yang, Danyi Li, Yuan Gao, Changxin Gao, Gui-Song Xia, Yuanqing Li, Li Liang, Jin-Gang Yu

In this paper, we propose to formulate annotation-efficient nucleus instance segmentation from the perspective of few-shot learning (FSL).

Few-Shot Learning Instance Segmentation +3

Generating, Reconstructing, and Representing Discrete and Continuous Data: Generalized Diffusion with Learnable Encoding-Decoding

no code implementations29 Feb 2024 Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian McAuley, Eric P. Xing, Zichao Yang, Zhiting Hu

The vast applications of deep generative models are anchored in three core capabilities -- generating new instances, reconstructing inputs, and learning compact representations -- across various data types, such as discrete text/protein sequences and continuous images.

Denoising

Non-Convex Stochastic Composite Optimization with Polyak Momentum

no code implementations5 Mar 2024 Yuan Gao, Anton Rodomanov, Sebastian U. Stich

In this paper, we focus on the stochastic proximal gradient method with Polyak momentum.

Enhancing Vision-Language Pre-training with Rich Supervisions

no code implementations5 Mar 2024 Yuan Gao, Kunyu Shi, Pengkai Zhu, Edouard Belval, Oren Nuriel, Srikar Appalaraju, Shabnam Ghadar, Vijay Mahadevan, Zhuowen Tu, Stefano Soatto

We propose Strongly Supervised pre-training with ScreenShots (S4) - a novel pre-training paradigm for Vision-Language Models using data from large-scale web screenshot rendering.

Table Detection

MEDBind: Unifying Language and Multimodal Medical Data Embeddings

no code implementations19 Mar 2024 Yuan Gao, SangWook Kim, David E Austin, Chris McIntosh

Medical vision-language pretraining models (VLPM) have achieved remarkable progress in fusing chest X-rays (CXR) with clinical texts, introducing image-text data binding approaches that enable zero-shot learning and downstream clinical tasks.

Language Modelling Large Language Model +2

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