b'Junzhou Huang'

research

∙ 06/21/2023

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks

It has been discovered that Graph Convolutional Networks (GCNs) encounte...

0 Jiaqi Han, et al. ∙

research

∙ 11/29/2022

Hierarchical Transformer for Survival Prediction Using Multimodality Whole Slide Images and Genomics

Learning good representation of giga-pixel level whole slide pathology i...

0 Chunyuan Li, et al. ∙

research

∙ 10/14/2022

Pareto-aware Neural Architecture Generation for Diverse Computational Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 09/27/2022

MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction

Retrosynthesis is a major task for drug discovery. It is formulated as a...

0 Jiahan Liu, et al. ∙

research

∙ 07/14/2022

ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images

Detectingandsegmentingobjectswithinwholeslideimagesis essential in compu...

0 Jiawei Yang, et al. ∙

research

∙ 06/23/2022

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

Graph instance contrastive learning has been proved as an effective task...

0 Xueyi Liu, et al. ∙

research

∙ 06/15/2022

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction

Recently, deep neural networks have greatly advanced undersampled Magnet...

0 Jiangpeng Yan, et al. ∙

research

∙ 05/20/2022

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection

Deep graph learning has achieved remarkable progresses in both business ...

0 Bingzhe Wu, et al. ∙

research

∙ 04/16/2022

DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup

Recently, federated learning has emerged as a promising approach for tra...

0 Bingzhe Wu, et al. ∙

research

∙ 03/31/2022

Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs

As a powerful tool for modeling complex relationships, hypergraphs are g...

0 Jiying Zhang, et al. ∙

research

∙ 03/21/2022

Boost Test-Time Performance with Closed-Loop Inference

Conventional deep models predict a test sample with a single forward pro...

7 Shuaicheng Niu, et al. ∙

research

∙ 03/12/2022

Equivariant Graph Mechanics Networks with Constraints

Learning to reason about relations and dynamics over multiple interactin...

0 Wenbing Huang, et al. ∙

research

∙ 02/21/2022

Vision-Language Pre-Training with Triple Contrastive Learning

Vision-language representation learning largely benefits from image-text...

10 Jinyu Yang, et al. ∙

research

∙ 02/17/2022

Transformer for Graphs: An Overview from Architecture Perspective

Recently, Transformer model, which has achieved great success in many ar...

0 Erxue Min, et al. ∙

research

∙ 02/15/2022

Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift

Deep graph learning (DGL) has achieved remarkable progress in both busin...

0 Bingzhe Wu, et al. ∙

research

∙ 01/25/2022

Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction

Click-Through Rate (CTR) prediction, is an essential component of online...

0 Erxue Min, et al. ∙

research

∙ 01/24/2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery – A Focus on Affinity Prediction Problems with Noise Annotations

AI-aided drug discovery (AIDD) is gaining increasing popularity due to i...

1 Yuanfeng Ji, et al. ∙

research

∙ 12/20/2021

RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction

The main target of retrosynthesis is to recursively decompose desired mo...

0 Chaochao Yan, et al. ∙

research

∙ 12/14/2021

Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis

Recently, generalization bounds of the non-convex empirical risk minimiz...

0 Bingzhe Wu, et al. ∙

research

∙ 12/01/2021

Graph Convolutional Module for Temporal Action Localization in Videos

Temporal action localization has long been researched in computer vision...

0 Runhao Zeng, et al. ∙

research

∙ 11/23/2021

CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning

Labels are costly and sometimes unreliable. Noisy label learning, semi-s...

0 Xin Zhang, et al. ∙

research

∙ 09/08/2021

Local Augmentation for Graph Neural Networks

Data augmentation has been widely used in image data and linguistic data...

1 Songtao Liu, et al. ∙

research

∙ 08/12/2021

TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...

0 Jinyu Yang, et al. ∙

research

∙ 06/17/2021

Frustratingly Easy Transferability Estimation

Transferability estimation has been an essential tool in selecting a pre...

3 Long-Kai Huang, et al. ∙

research

∙ 06/14/2021

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels

Semi-supervised node classification, as a fundamental problem in graph l...

0 Xuefeng Du, et al. ∙

research

∙ 06/05/2021

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations

Valuation problems, such as attribution-based feature interpretation, da...

0 Yatao Bian, et al. ∙

research

∙ 05/29/2021

Learning Graphon Autoencoders for Generative Graph Modeling

Graphon is a nonparametric model that generates graphs with arbitrary si...

0 Hongteng Xu, et al. ∙

research

∙ 05/26/2021

Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge

With the success of the graph embedding model in both academic and indus...

0 Heng Chang, et al. ∙

research

∙ 05/23/2021

Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation

Recent studies imply that deep neural networks are vulnerable to adversa...

0 Jinyu Yang, et al. ∙

research

∙ 05/11/2021

EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models

Accurate protein structure prediction from amino-acid sequences is criti...

0 Jiaxiang Wu, et al. ∙

research

∙ 05/10/2021

tFold-TR: Combining Deep Learning Enhanced Hybrid Potential Energy for Template-Based Modelling Structure Refinement

Proteins structure prediction has long been a grand challenge over the p...

0 Liangzhen Zheng, et al. ∙

research

∙ 04/14/2021

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

Graph Neural Network (GNN) research is rapidly growing thanks to the cap...

54 Chaoyang He, et al. ∙

research

∙ 04/08/2021

QD-GCN: Query-Driven Graph Convolutional Networks for Attributed Community Search

Recently, attributed community search, a related but different problem t...

4 Yuli Jiang, et al. ∙

research

∙ 04/07/2021

Deep Implicit Statistical Shape Models for 3D Medical Image Delineation

3D delineation of anatomical structures is a cardinal goal in medical im...

0 Ashwin Raju, et al. ∙

research

∙ 03/20/2021

Recognizing Predictive Substructures with Subgraph Information Bottleneck

The emergence of Graph Convolutional Network (GCN) has greatly boosted t...

0 Junchi Yu, et al. ∙

research

∙ 03/17/2021

Diversified Multiscale Graph Learning with Graph Self-Correction

Though the multiscale graph learning techniques have enabled advanced fe...

0 Yuzhao Chen, et al. ∙

research

∙ 02/27/2021

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets

Designing feasible and effective architectures under diverse computation...

0 Yong Guo, et al. ∙

research

∙ 02/20/2021

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Designing effective architectures is one of the key factors behind the s...

0 Yong Guo, et al. ∙

research

∙ 02/03/2021

Learning Diverse-Structured Networks for Adversarial Robustness

In adversarial training (AT), the main focus has been the objective and ...

1 Xuefeng Du, et al. ∙

research

∙ 01/22/2021

Towards Expectation-Maximization by SQL in RDBMS

Integrating machine learning techniques into RDBMSs is an important task...

0 Kangfei Zhao, et al. ∙

research

∙ 12/16/2020

Hierarchical Graph Capsule Network

Graph Neural Networks (GNNs) draw their strength from explicitly modelin...

0 Jinyu Yang, et al. ∙

research

∙ 11/10/2020

Deep Multimodal Fusion by Channel Exchanging

Deep multimodal fusion by using multiple sources of data for classificat...

8 Yikai Wang, et al. ∙

research

∙ 11/04/2020

On Self-Distilling Graph Neural Network

Recently, the teacher-student knowledge distillation framework has demon...

0 Yuzhao Chen, et al. ∙

research

∙ 11/04/2020

RetroXpert: Decompose Retrosynthesis Prediction like a Chemist

Retrosynthesis is the process of recursively decomposing target molecule...

7 Chaochao Yan, et al. ∙

research

∙ 10/12/2020

Graph Information Bottleneck for Subgraph Recognition

Given the input graph and its label/property, several key problems of gr...

0 Junchi Yu, et al. ∙

research

∙ 09/23/2020

Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networks

Traditional image-based survival prediction models rely on discriminativ...

12 Jiawen Yao, et al. ∙

research

∙ 09/15/2020

Microscope Based HER2 Scoring System

The overexpression of human epidermal growth factor receptor 2 (HER2) ha...

0 Jun Zhang, et al. ∙

research

∙ 09/05/2020

User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation

Mask-based annotation of medical images, especially for 3D data, is a bo...

0 Ashwin Raju, et al. ∙

research

∙ 08/22/2020

Tackling Over-Smoothing for General Graph Convolutional Networks

Increasing the depth of Graph Convolutional Networks (GCN), which in pri...

0 Wenbing Huang, et al. ∙

research

∙ 07/28/2020

Improving Generative Adversarial Networks with Local Coordinate Coding

Generative adversarial networks (GANs) have shown remarkable success in ...

4 Jiezhang Cao, et al. ∙

Junzhou Huang

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