research
∙
06/21/2023
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks
It has been discovered that Graph Convolutional Networks (GCNs) encounte...
share
research
∙
06/18/2023
Vision Guided MIMO Radar Beamforming for Enhanced Vital Signs Detection in Crowds
Radar as a remote sensing technology has been used to analyze human acti...
research
∙
03/04/2023
Decision Support System for Chronic Diseases Based on Drug-Drug Interactions
Many patients with chronic diseases resort to multiple medications to re...
research
∙
10/20/2022
Vertical Federated Linear Contextual Bandits
In this paper, we investigate a novel problem of building contextual ban...
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...
research
∙
06/11/2022
Semi-Supervised Hierarchical Graph Classification
Node classification and graph classification are two graph learning prob...
research
∙
05/25/2022
Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis
The ability to synthesize long-term human motion sequences in real-world...
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 ...
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...
research
∙
03/20/2022
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport
Recently, the pretrain-finetuning paradigm has attracted tons of attenti...
research
∙
03/15/2022
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
After the great success of Vision Transformer variants (ViTs) in compute...
research
∙
03/12/2022
Equivariant Graph Mechanics Networks with Constraints
Learning to reason about relations and dynamics over multiple interactin...
research
∙
02/22/2022
Equivariant Graph Hierarchy-Based Neural Networks
Equivariant Graph neural Networks (EGNs) are powerful in characterizing ...
research
∙
02/17/2022
Transformer for Graphs: An Overview from Architecture Perspective
Recently, Transformer model, which has achieved great success in many ar...
research
∙
02/15/2022
Geometrically Equivariant Graph Neural Networks: A Survey
Many scientific problems require to process data in the form of geometri...
research
∙
01/25/2022
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction
Click-Through Rate (CTR) prediction, is an essential component of online...
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...
research
∙
12/01/2021
Graph Convolutional Module for Temporal Action Localization in Videos
Temporal action localization has long been researched in computer vision...
research
∙
11/01/2021
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements
3D interacting hand reconstruction is essential to facilitate human-mach...
research
∙
10/17/2021
VoteHMR: Occlusion-Aware Voting Network for Robust 3D Human Mesh Recovery from Partial Point Clouds
3D human mesh recovery from point clouds is essential for various tasks,...
research
∙
09/08/2021
Local Augmentation for Graph Neural Networks
Data augmentation has been widely used in image data and linguistic data...
research
∙
08/13/2021
FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integration
Most existing monocular 3D pose estimation approaches only focus on a si...
research
∙
06/17/2021
Frustratingly Easy Transferability Estimation
Transferability estimation has been an essential tool in selecting a pre...
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...
research
∙
06/11/2021
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising
In online advertising, auto-bidding has become an essential tool for adv...
research
∙
06/07/2021
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
In e-commerce advertising, it is crucial to jointly consider various per...
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...
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...
research
∙
05/23/2021
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Recent studies imply that deep neural networks are vulnerable to adversa...
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...
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...
research
∙
03/20/2021
Recognizing Predictive Substructures with Subgraph Information Bottleneck
The emergence of Graph Convolutional Network (GCN) has greatly boosted t...
research
∙
03/17/2021
Diversified Multiscale Graph Learning with Graph Self-Correction
Though the multiscale graph learning techniques have enabled advanced fe...
research
∙
02/03/2021
Learning Diverse-Structured Networks for Adversarial Robustness
In adversarial training (AT), the main focus has been the objective and ...
research
∙
01/22/2021
Towards Expectation-Maximization by SQL in RDBMS
Integrating machine learning techniques into RDBMSs is an important task...
research
∙
12/29/2020
Chasing the Tail in Monocular 3D Human Reconstruction with Prototype Memory
Deep neural networks have achieved great progress in single-image 3D hum...
research
∙
12/16/2020
Hierarchical Graph Capsule Network
Graph Neural Networks (GNNs) draw their strength from explicitly modelin...
research
∙
11/10/2020
Deep Multimodal Fusion by Channel Exchanging
Deep multimodal fusion by using multiple sources of data for classificat...
research
∙
11/04/2020
On Self-Distilling Graph Neural Network
Recently, the teacher-student knowledge distillation framework has demon...
research
∙
10/12/2020
Graph Information Bottleneck for Subgraph Recognition
Given the input graph and its label/property, several key problems of gr...
research
∙
10/09/2020
Dirichlet Graph Variational Autoencoder
Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have be...
research
∙
08/28/2020
Pixel-Face: A Large-Scale, High-Resolution Benchmark for 3D Face Reconstruction
3D face reconstruction is a fundamental task that can facilitate numerou...
research
∙
08/22/2020
Tackling Over-Smoothing for General Graph Convolutional Networks
Increasing the depth of Graph Convolutional Networks (GCN), which in pri...
research
∙
08/19/2020
FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration
Although the essential nuance of human motion is often conveyed as a com...
research
∙
07/12/2020
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Graph Identification (GI) has long been researched in graph learning and...
research
∙
06/01/2020
Leveraging TSP Solver Complementarity via Deep Learning
The Travelling Salesman Problem (TSP) is a classical NP-hard problem and...
research
∙
03/16/2020
Spectral Graph Attention Network
Variants of Graph Neural Networks (GNNs) for representation learning hav...
research
∙
02/04/2020
Graph Representation Learning via Graphical Mutual Information Maximization
The richness in the content of various information networks such as soci...
research
∙
01/22/2020
Adversarial Attack on Community Detection by Hiding Individuals
It has been demonstrated that adversarial graphs, i.e., graphs with impe...
research
∙
01/17/2020