b'Xiang Zhang'

research

∙ 08/29/2023

Robot Manipulation Task Learning by Leveraging SE(3) Group Invariance and Equivariance

This paper presents a differential geometric control approach that lever...

0 Joohwan Seo, et al. ∙

research

∙ 08/11/2023

Generalizing Event-Based Motion Deblurring in Real-World Scenarios

Event-based motion deblurring has shown promising results by exploiting ...

0 Xiang Zhang, et al. ∙

research

∙ 07/04/2023

Random Walk on Multiple Networks

Random Walk is a basic algorithm to explore the structure of networks, w...

0 Dongsheng Luo, et al. ∙

research

∙ 06/26/2023

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

Brain graphs, which model the structural and functional relationships be...

0 Gaotang Li, et al. ∙

research

∙ 06/13/2023

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations

Imitation learning has achieved great success in many sequential decisio...

0 Tianxiang Zhao, et al. ∙

research

∙ 06/05/2023

MotionTrack: Learning Motion Predictor for Multiple Object Tracking

Significant advancements have been made in multi-object tracking (MOT) w...

0 Changcheng Xiao, et al. ∙

research

∙ 05/29/2023

ReSup: Reliable Label Noise Suppression for Facial Expression Recognition

Because of the ambiguous and subjective property of the facial expressio...

0 Xiang Zhang, et al. ∙

research

∙ 05/26/2023

GC-Flow: A Graph-Based Flow Network for Effective Clustering

Graph convolutional networks (GCNs) are discriminative models that direc...

0 Tianchun Wang, et al. ∙

research

∙ 05/16/2023

Power Grid Transient Analysis via Open-Source Circuit Simulator: A Case Study of HVDC

This paper proposes an electronic circuit simulator-based method to acce...

0 Yongli Zhu, et al. ∙

research

∙ 05/04/2023

Learning Generalizable Pivoting Skills

The skill of pivoting an object with a robotic system is challenging for...

0 Xiang Zhang, et al. ∙

research

∙ 04/18/2023

TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models

Data augmentation has been established as an efficacious approach to sup...

3 Yuwei Yin, et al. ∙

research

∙ 04/14/2023

Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events

Scene Dynamic Recovery (SDR) by inverting distorted Rolling Shutter (RS)...

0 Yangguang Wang, et al. ∙

research

∙ 04/05/2023

Recovering Continuous Scene Dynamics from A Single Blurry Image with Events

This paper aims at demystifying a single motion-blurred image with event...

0 Zhangyi Cheng, et al. ∙

research

∙ 04/03/2023

Enhancing Clinical Evidence Recommendation with Multi-Channel Heterogeneous Learning on Evidence Graphs

Clinical evidence encompasses the associations and impacts between patie...

0 Maolin Luo, et al. ∙

research

∙ 04/03/2023

A Hierarchical Multi-Vehicle Coordinated Motion Planning Method based on Interactive Spatio-Temporal Corridors

Multi-vehicle coordinated motion planning has always been challenged to ...

0 Xiang Zhang, et al. ∙

research

∙ 03/31/2023

Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understanding

Contrastive learning has shown promising potential for learning robust r...

0 Xiang Zhang, et al. ∙

research

∙ 03/21/2023

Time Series Contrastive Learning with Information-Aware Augmentations

Various contrastive learning approaches have been proposed in recent yea...

2 Dongsheng Luo, et al. ∙

research

∙ 02/27/2023

Learning to Super-Resolve Blurry Images with Events

Super-Resolution from a single motion Blurred image (SRB) is a severely ...

0 Lei Yu, et al. ∙

research

∙ 02/11/2023

Unnoticeable Backdoor Attacks on Graph Neural Networks

Graph Neural Networks (GNNs) have achieved promising results in various ...

0 Enyan Dai, et al. ∙

research

∙ 02/06/2023

Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval

In Composed Image Retrieval (CIR), a user combines a query image with te...

0 Kuniaki Saito, et al. ∙

research

∙ 01/25/2023

Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective

Recently, graph-based models designed for downstream tasks have signific...

0 Jiayuan Chen, et al. ∙

research

∙ 01/07/2023

Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment

Uncovering rationales behind predictions of graph neural networks (GNNs)...

8 Tianxiang Zhao, et al. ∙

research

∙ 12/16/2022

TopoImb: Toward Topology-level Imbalance in Learning from Graphs

Graph serves as a powerful tool for modeling data that has an underlying...

0 Tianxiang Zhao, et al. ∙

research

∙ 12/05/2022

Learning to See Through with Events

Although synthetic aperture imaging (SAI) can achieve the seeing-through...

0 Lei Yu, et al. ∙

research

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

research

∙ 10/26/2022

Personalized Federated Learning via Heterogeneous Modular Networks

Personalized Federated Learning (PFL) which collaboratively trains a fed...

0 Tianchun Wan, et al. ∙

research

∙ 09/25/2022

Multimodal Learning with Channel-Mixing and Masked Autoencoder on Facial Action Unit Detection

Recent studies utilizing multi-modal data aimed at building a robust mod...

0 Xiang Zhang, et al. ∙

research

∙ 08/03/2022

Link Prediction on Heterophilic Graphs via Disentangled Representation Learning

Link prediction is an important task that has wide applications in vario...

7 Shijie Zhou, et al. ∙

research

∙ 06/17/2022

Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

Pre-training on time series poses a unique challenge due to the potentia...

0 Xiang Zhang, et al. ∙

research

∙ 06/10/2022

Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks

In recent years, graph neural networks (GNNs) have achieved state-of-the...

0 Tianxiang Zhao, et al. ∙

research

∙ 06/02/2022

Prefix Conditioning Unifies Language and Label Supervision

Vision-language contrastive learning suggests a new learning paradigm by...

0 Kuniaki Saito, et al. ∙

research

∙ 05/28/2022

A Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization

Sentence summarization aims at compressing a long sentence into a short ...

0 Puyuan Liu, et al. ∙

research

∙ 05/27/2022

On Consistency in Graph Neural Network Interpretation

Uncovering rationales behind predictions of graph neural networks (GNNs)...

15 Tianxiang Zhao, et al. ∙

research

∙ 04/21/2022

Multi-scale Knowledge Distillation for Unsupervised Person Re-Identification

Unsupervised person re-identification is a challenging and promising tas...

0 Long Lan, et al. ∙

research

∙ 04/12/2022

On the Equity of Nuclear Norm Maximization in Unsupervised Domain Adaptation

Nuclear norm maximization has shown the power to enhance the transferabi...

0 Wenju Zhang, et al. ∙

research

∙ 04/05/2022

Text Spotting Transformers

In this paper, we present TExt Spotting TRansformers (TESTR), a generic ...

6 Xiang Zhang, et al. ∙

research

∙ 03/30/2022

Knowledge-Spreader: Learning Facial Action Unit Dynamics with Extremely Limited Labels

Recent studies on the automatic detection of facial action unit (AU) hav...

0 Xiaotian Li, et al. ∙

research

∙ 03/29/2022

An EEG-Based Multi-Modal Emotion Database with Both Posed and Authentic Facial Actions for Emotion Analysis

Emotion is an experience associated with a particular pattern of physiol...

0 Xiaotian Li, et al. ∙

research

∙ 03/28/2022

Offline-Online Learning of Deformation Model for Cable Manipulation with Graph Neural Networks

Manipulating deformable linear objects by robots has a wide range of app...

0 Changhao Wang, et al. ∙

research

∙ 03/23/2022

Unifying Motion Deblurring and Frame Interpolation with Events

Slow shutter speed and long exposure time of frame-based cameras often c...

0 Xiang Zhang, et al. ∙

research

∙ 03/22/2022

Multi-Modal Learning for AU Detection Based on Multi-Head Fused Transformers

Multi-modal learning has been intensified in recent years, especially fo...

0 Xiang Zhang, et al. ∙

research

∙ 02/23/2022

Exploring Edge Disentanglement for Node Classification

Edges in real-world graphs are typically formed by a variety of factors ...

0 Tianxiang Zhao, et al. ∙

research

∙ 01/29/2022

AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models

Knowledge distillation (KD) methods compress large models into smaller s...

6 Dongkuan Xu, et al. ∙

research

∙ 12/06/2021

Using principal stratification in analysis of clinical trials

The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as...

0 Ilya Lipkovich, et al. ∙

research

∙ 11/01/2021

Safe Online Gain Optimization for Variable Impedance Control

Smooth behaviors are preferable for many contact-rich manipulation tasks...

0 Changhao Wang, et al. ∙

research

∙ 10/28/2021

InfoGCL: Information-Aware Graph Contrastive Learning

Various graph contrastive learning models have been proposed to improve ...

5 Dongkuan Xu, et al. ∙

research

∙ 10/25/2021

Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Tasks

This paper introduces a discrete-continuous action space to learn insert...

0 Xiang Zhang, et al. ∙

research

∙ 10/17/2021

A Q-Learning-based Approach for Distributed Beam Scheduling in mmWave Networks

We consider the problem of distributed downlink beam scheduling and powe...

0 Xiang Zhang, et al. ∙

research

∙ 10/11/2021

Graph-Guided Network for Irregularly Sampled Multivariate Time Series

In many domains, including healthcare, biology, and climate science, tim...

0 Xiang Zhang, et al. ∙

research

∙ 10/11/2021

Online Graph Learning in Dynamic Environments

Inferring the underlying graph topology that characterizes structured da...

0 Xiang Zhang, et al. ∙

Xiang Zhang

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