Search Results for author: Wenbing Huang

Found 70 papers, 33 papers with code

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks

no code implementations21 Jun 2023 Jiaqi Han, Wenbing Huang, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

Regarding the layer-dependent sampler, we interestingly find that increasingly sampling edges from the bottom layer yields superior performance than the decreasing counterpart as well as DropEdge.

Node Classification

Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning

no code implementations2 Jun 2023 Xiangzhe Kong, Wenbing Huang, Yang Liu

Many processes in biology and drug discovery involve various 3D interactions between different molecules, such as protein and protein, protein and small molecule, etc.

Drug Discovery

Subequivariant Graph Reinforcement Learning in 3D Environments

1 code implementation30 May 2023 Runfa Chen, Jiaqi Han, Fuchun Sun, Wenbing Huang

Learning a shared policy that guides the locomotion of different agents is of core interest in Reinforcement Learning (RL), which leads to the study of morphology-agnostic RL.

reinforcement-learning Reinforcement Learning (RL)

Compacting Binary Neural Networks by Sparse Kernel Selection

no code implementations CVPR 2023 Yikai Wang, Wenbing Huang, Yinpeng Dong, Fuchun Sun, Anbang Yao

Binary Neural Network (BNN) represents convolution weights with 1-bit values, which enhances the efficiency of storage and computation.


End-to-End Full-Atom Antibody Design

1 code implementation1 Feb 2023 Xiangzhe Kong, Wenbing Huang, Yang Liu

Finally, the updated antibody is docked to the epitope via the alignment of the shadow paratope.

Learning Active Camera for Multi-Object Navigation

no code implementations14 Oct 2022 Peihao Chen, Dongyu Ji, Kunyang Lin, Weiwen Hu, Wenbing Huang, Thomas H. Li, Mingkui Tan, Chuang Gan

How to make robots perceive the environment as efficiently as humans is a fundamental problem in robotics.


Benefits of Permutation-Equivariance in Auction Mechanisms

no code implementations11 Oct 2022 Tian Qin, Fengxiang He, Dingfeng Shi, Wenbing Huang, DaCheng Tao

Designing an incentive-compatible auction mechanism that maximizes the auctioneer's revenue while minimizes the bidders' ex-post regret is an important yet intricate problem in economics.

Planning Assembly Sequence with Graph Transformer

1 code implementation11 Oct 2022 Lin Ma, Jiangtao Gong, Hao Xu, Hao Chen, Hao Zhao, Wenbing Huang, Guyue Zhou

In this paper, we present a graph-transformer based framework for the ASP problem which is trained and demonstrated on a self-collected ASP database.

Bridged Transformer for Vision and Point Cloud 3D Object Detection

1 code implementation CVPR 2022 Yikai Wang, TengQi Ye, Lele Cao, Wenbing Huang, Fuchun Sun, Fengxiang He, DaCheng Tao

Recently, there is a trend of leveraging multiple sources of input data, such as complementing the 3D point cloud with 2D images that often have richer color and fewer noises.

3D Object Detection object-detection

Conditional Antibody Design as 3D Equivariant Graph Translation

1 code implementation12 Aug 2022 Xiangzhe Kong, Wenbing Huang, Yang Liu

Specifically, the relative improvement to baselines is about 23% in antigen-binding CDR design and 34% for affinity optimization.


Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs

2 code implementations18 Jul 2022 Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

Pretraining molecular representation models without labels is fundamental to various applications.

molecular representation

Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training

no code implementations NeurIPS 2021 Xueyi Liu, Yu Rong, Tingyang Xu, Fuchun Sun, Wenbing Huang, Junzhou Huang

To remedy this issue, we propose to select positive graph instances directly from existing graphs in the training set, which ultimately maintains the legality and similarity to the target graphs.

Contrastive Learning Graph Classification +1

SNAKE: Shape-aware Neural 3D Keypoint Field

1 code implementation3 Jun 2022 Chengliang Zhong, Peixing You, Xiaoxue Chen, Hao Zhao, Fuchun Sun, Guyue Zhou, Xiaodong Mu, Chuang Gan, Wenbing Huang

Detecting 3D keypoints from point clouds is important for shape reconstruction, while this work investigates the dual question: can shape reconstruction benefit 3D keypoint detection?

Keypoint Detection

Multimodal Token Fusion for Vision Transformers

7 code implementations CVPR 2022 Yikai Wang, Xinghao Chen, Lele Cao, Wenbing Huang, Fuchun Sun, Yunhe Wang

Many adaptations of transformers have emerged to address the single-modal vision tasks, where self-attention modules are stacked to handle input sources like images.

3D Object Detection Image-to-Image Translation +2

Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation

1 code implementation15 Mar 2022 Runfa Chen, Yu Rong, Shangmin Guo, Jiaqi Han, Fuchun Sun, Tingyang Xu, Wenbing Huang

After the great success of Vision Transformer variants (ViTs) in computer vision, it has also demonstrated great potential in domain adaptive semantic segmentation.

Pseudo Label Synthetic-to-Real Translation +1

Equivariant Graph Mechanics Networks with Constraints

1 code implementation12 Mar 2022 Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

The core of GMN is that it represents, by generalized coordinates, the forward kinematics information (positions and velocities) of a structural object.

Equivariant Graph Hierarchy-Based Neural Networks

1 code implementation22 Feb 2022 Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

Equivariant Graph neural Networks (EGNs) are powerful in characterizing the dynamics of multi-body physical systems.

Sound Adversarial Audio-Visual Navigation

1 code implementation ICLR 2022 Yinfeng Yu, Wenbing Huang, Fuchun Sun, Changan Chen, Yikai Wang, Xiaohong Liu

In this work, we design an acoustically complex environment in which, besides the target sound, there exists a sound attacker playing a zero-sum game with the agent.

Navigate Visual Navigation

Transformer for Graphs: An Overview from Architecture Perspective

1 code implementation17 Feb 2022 Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong

In this survey, we provide a comprehensive review of various Graph Transformer models from the architectural design perspective.

Geometrically Equivariant Graph Neural Networks: A Survey

no code implementations15 Feb 2022 Jiaqi Han, Yu Rong, Tingyang Xu, Wenbing Huang

Many scientific problems require to process data in the form of geometric graphs.

Inductive Bias

Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction

1 code implementation4 Dec 2021 Yikai Wang, Fuchun Sun, Wenbing Huang, Fengxiang He, DaCheng Tao

For the application of dense image prediction, the validity of CEN is tested by four different scenarios: multimodal fusion, cycle multimodal fusion, multitask learning, and multimodal multitask learning.

Semantic Segmentation

Graph Convolutional Module for Temporal Action Localization in Videos

no code implementations1 Dec 2021 Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan

To this end, we propose a general graph convolutional module (GCM) that can be easily plugged into existing action localization methods, including two-stage and one-stage paradigms.

Ranked #2 on Temporal Action Localization on THUMOS’14 (mAP IOU@0.1 metric)

Action Recognition Temporal Action Localization

Weakly Supervised Graph Clustering

no code implementations29 Sep 2021 Tian Bian, Tingyang Xu, Yu Rong, Wenbing Huang, Xi Xiao, Peilin Zhao, Junzhou Huang, Hong Cheng

Graph Clustering, which clusters the nodes of a graph given its collection of node features and edge connections in an unsupervised manner, has long been researched in graph learning and is essential in certain applications.

Clustering Graph Clustering +1

Constrained Graph Mechanics Networks

no code implementations ICLR 2022 Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

In this manner, the geometrical constraints are implicitly and naturally encoded in the forward kinematics.

PI-GNN: Towards Robust Semi-Supervised Node Classification against Noisy Labels

no code implementations29 Sep 2021 Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Junzhou Huang

Semi-supervised node classification on graphs is a fundamental problem in graph mining that uses a small set of labeled nodes and many unlabeled nodes for training, so that its performance is quite sensitive to the quality of the node labels.

Graph Mining Node Classification

Elastic Tactile Simulation Towards Tactile-Visual Perception

1 code implementation11 Aug 2021 Yikai Wang, Wenbing Huang, Bin Fang, Fuchun Sun, Chang Li

By contrast, EIP models the tactile sensor as a group of coordinated particles, and the elastic property is applied to regulate the deformation of particles during contact.

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

1 code implementation14 Jun 2021 Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang

This paper bridges the gap by proposing a pairwise framework for noisy node classification on graphs, which relies on the PI as a primary learning proxy in addition to the pointwise learning from the noisy node class labels.

Contrastive Learning Graph Learning +2

Adversarial Option-Aware Hierarchical Imitation Learning

1 code implementation10 Jun 2021 Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei LI

In particular, we propose an Expectation-Maximization(EM)-style algorithm: an E-step that samples the options of expert conditioned on the current learned policy, and an M-step that updates the low- and high-level policies of agent simultaneously to minimize the newly proposed option-occupancy measurement between the expert and the agent.

Imitation Learning

Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge

no code implementations26 May 2021 Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Xin Wang, Wenwu Zhu, Junzhou Huang

We investigate the theoretical connections between graph signal processing and graph embedding models and formulate the graph embedding model as a general graph signal process with a corresponding graph filter.

Adversarial Attack Graph Embedding +1

Elastic Interaction of Particles for Robotic Tactile Simulation

no code implementations23 Nov 2020 Yikai Wang, Wenbing Huang, Bin Fang, Fuchun Sun

At its core, EIP models the tactile sensor as a group of coordinated particles, and the elastic theory is applied to regulate the deformation of particles during the contact process.

Deep Multimodal Fusion by Channel Exchanging

1 code implementation NeurIPS 2020 Yikai Wang, Wenbing Huang, Fuchun Sun, Tingyang Xu, Yu Rong, Junzhou Huang

Deep multimodal fusion by using multiple sources of data for classification or regression has exhibited a clear advantage over the unimodal counterpart on various applications.

Image-to-Image Translation Semantic Segmentation +1

Tackling Over-Smoothing for General Graph Convolutional Networks

no code implementations22 Aug 2020 Wenbing Huang, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

Increasing the depth of GCN, which is expected to permit more expressivity, is shown to incur performance detriment especially on node classification.

Node Classification

Towards Purely Unsupervised Disentanglement of Appearance and Shape for Person Images Generation

no code implementations26 Jul 2020 Hongtao Yang, Tong Zhang, Wenbing Huang, Xuming He, Fatih Porikli

To be clear, in this paper, we refer unsupervised learning as learning without task-specific human annotations, pairs or any form of weak supervision.)


Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?

no code implementations12 Jul 2020 Tian Bian, Xi Xiao, Tingyang Xu, Yu Rong, Wenbing Huang, Peilin Zhao, Junzhou Huang

Upon a formal discussion of the variants of IGI, we choose a particular case study of node clustering by making use of the graph labels and node features, with an assistance of a hierarchical graph that further characterizes the connections between different graphs.

Clustering Community Detection +3

Self-Supervised Graph Transformer on Large-Scale Molecular Data

3 code implementations NeurIPS 2020 Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying WEI, Wenbing Huang, Junzhou Huang

We pre-train GROVER with 100 million parameters on 10 million unlabelled molecules -- the biggest GNN and the largest training dataset in molecular representation learning.

Molecular Property Prediction molecular representation +2

Multi-View Graph Neural Networks for Molecular Property Prediction

no code implementations17 May 2020 Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye, Junzhou Huang

Guided by this observation, we present Multi-View Graph Neural Network (MV-GNN), a multi-view message passing architecture to enable more accurate predictions of molecular properties.

Drug Discovery Molecular Property Prediction +1

Dense Regression Network for Video Grounding

1 code implementation CVPR 2020 Runhao Zeng, Haoming Xu, Wenbing Huang, Peihao Chen, Mingkui Tan, Chuang Gan

The key idea of this paper is to use the distances between the frame within the ground truth and the starting (ending) frame as dense supervisions to improve the video grounding accuracy.

Natural Language Moment Retrieval Natural Language Queries +2

Spectral Graph Attention Network with Fast Eigen-approximation

no code implementations16 Mar 2020 Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Somayeh Sojoudi, Junzhou Huang, Wenwu Zhu

In this paper, we first introduce the attention mechanism in the spectral domain of graphs and present Spectral Graph Attention Network (SpGAT) that learns representations for different frequency components regarding weighted filters and graph wavelets bases.

Graph Attention Node Classification +1

Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

2 code implementations CVPR 2020 Runfa Chen, Wenbing Huang, Binghui Huang, Fuchun Sun, Bin Fang

The proposed architecture, termed as NICE-GAN, exhibits two advantageous patterns over previous approaches: First, it is more compact since no independent encoding component is required; Second, this plug-in encoder is directly trained by the adversary loss, making it more informative and trained more effectively if a multi-scale discriminator is applied.

Translation Unsupervised Image-To-Image Translation

Graph Representation Learning via Graphical Mutual Information Maximization

1 code implementation4 Feb 2020 Zhen Peng, Wenbing Huang, Minnan Luo, Qinghua Zheng, Yu Rong, Tingyang Xu, Junzhou Huang

The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expressive representations without external supervision.

Graph Representation Learning Link Prediction +2

Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks

1 code implementation17 Jan 2020 Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang

Meanwhile, detecting rumors from such massive information in social media is becoming an arduous challenge.

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

no code implementations16 Nov 2019 Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Chao Yang, Bin Fang, Huaping Liu

In this paper, we study Reinforcement Learning from Demonstrations (RLfD) that improves the exploration efficiency of Reinforcement Learning (RL) by providing expert demonstrations.

reinforcement-learning Reinforcement Learning (RL)

Graph Convolutional Networks for Temporal Action Localization

1 code implementation ICCV 2019 Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan

Then we apply the GCNs over the graph to model the relations among different proposals and learn powerful representations for the action classification and localization.

Ranked #4 on Temporal Action Localization on THUMOS’14 (mAP IOU@0.1 metric)

Action Classification Temporal Action Localization

A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models

1 code implementation4 Aug 2019 Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang

To this end, we begin by investigating the theoretical connections between graph signal processing and graph embedding models in a principled way and formulate the graph embedding model as a general graph signal process with corresponding graph filter.

Adversarial Attack Graph Embedding +2

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

6 code implementations ICLR 2020 Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang

\emph{Over-fitting} and \emph{over-smoothing} are two main obstacles of developing deep Graph Convolutional Networks (GCNs) for node classification.

Classification General Classification +1

Label-Aware Graph Convolutional Networks

no code implementations10 Jul 2019 Hao Chen, Yue Xu, Feiran Huang, Zengde Deng, Wenbing Huang, Senzhang Wang, Peng He, Zhoujun Li

In this paper, we consider the problem of node classification and propose the Label-Aware Graph Convolutional Network (LAGCN) framework which can directly identify valuable neighbors to enhance the performance of existing GCN models.

General Classification Graph Classification +2

Unsupervised Adversarial Graph Alignment with Graph Embedding

no code implementations1 Jul 2019 Chaoqi Chen, Weiping Xie, Tingyang Xu, Yu Rong, Wenbing Huang, Xinghao Ding, Yue Huang, Junzhou Huang

In this paper, we propose an Unsupervised Adversarial Graph Alignment (UAGA) framework to learn a cross-graph alignment between two embedding spaces of different graphs in a fully unsupervised fashion (\emph{i. e.,} no existing anchor links and no users' personal profile or attribute information is available).

Graph Embedding Link Prediction

Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs

1 code implementation27 Jun 2019 Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi

Existing techniques either cannot be scaled to large-scale bipartite graphs that have limited labels or cannot exploit the unique structure of bipartite graphs, which have distinct node features in two domains.

Recommendation Systems Representation Learning

Neural Collaborative Subspace Clustering

no code implementations24 Apr 2019 Tong Zhang, Pan Ji, Mehrtash Harandi, Wenbing Huang, Hongdong Li

We introduce the Neural Collaborative Subspace Clustering, a neural model that discovers clusters of data points drawn from a union of low-dimensional subspaces.


Semi-Supervised Graph Classification: A Hierarchical Graph Perspective

1 code implementation10 Apr 2019 Jia Li, Yu Rong, Hong Cheng, Helen Meng, Wenbing Huang, Junzhou Huang

We study the node classification problem in the hierarchical graph where a `node' is a graph instance, e. g., a user group in the above example.

General Classification Graph Classification +3

Weakly Supervised Dense Event Captioning in Videos

no code implementations NeurIPS 2018 Xuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang, Wenwu Zhu, Junzhou Huang

Dense event captioning aims to detect and describe all events of interest contained in a video.

PocketFlow: An Automated Framework for Compressing and Accelerating Deep Neural Networks

1 code implementation NIPS Workshop CDNNRIA 2018 Jiaxiang Wu, Yao Zhang, Haoli Bai, Huasong Zhong, Jinlong Hou, Wei Liu, Wenbing Huang, Junzhou Huang

Deep neural networks are widely used in various domains, but the prohibitive computational complexity prevents their deployment on mobile devices.

Model Compression

Deep Feature Pyramid Reconfiguration for Object Detection

no code implementations ECCV 2018 Tao Kong, Fuchun Sun, Wenbing Huang, Huaping Liu

In this paper, we begin by investigating current feature pyramids solutions, and then reformulate the feature pyramid construction as the feature reconfiguration process.

object-detection Object Detection

Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation

no code implementations9 Aug 2018 Lijie Fan, Wenbing Huang, Chuang Gan, Junzhou Huang, Boqing Gong

The recent advances in deep learning have made it possible to generate photo-realistic images by using neural networks and even to extrapolate video frames from an input video clip.

Facial expression generation Image-to-Image Translation +2

Task Transfer by Preference-Based Cost Learning

no code implementations12 May 2018 Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu

The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task.

End-to-End Learning of Motion Representation for Video Understanding

1 code implementation CVPR 2018 Lijie Fan, Wenbing Huang, Chuang Gan, Stefano Ermon, Boqing Gong, Junzhou Huang

Despite the recent success of end-to-end learned representations, hand-crafted optical flow features are still widely used in video analysis tasks.

Action Recognition Optical Flow Estimation +1

Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data

no code implementations20 Oct 2017 Kun Liu, Wu Liu, Huadong Ma, Wenbing Huang, Xiongxiong Dong

Motivated by this, we study the task of action recognition in surveillance video under a more realistic \emph{generalized zero-shot setting}, where testing data contains both seen and unseen classes.

Action Recognition Generalized Zero-Shot Learning +1

Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning

no code implementations3 Aug 2016 Wenbing Huang, Fuchun Sun, Lele Cao, Mehrtash Harandi

We then devise efficient algorithms to perform sparse coding and dictionary learning on the space of infinite-dimensional subspaces.

Dictionary Learning General Classification +5

Sparse Coding and Dictionary Learning With Linear Dynamical Systems

no code implementations CVPR 2016 Wenbing Huang, Fuchun Sun, Lele Cao, Deli Zhao, Huaping Liu, Mehrtash Harandi

To enhance the performance of LDSs, in this paper, we address the challenging issue of performing sparse coding on the space of LDSs, where both data and dictionary atoms are LDSs.

Dictionary Learning Video Classification

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