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06/21/2023
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks
It has been discovered that Graph Convolutional Networks (GCNs) encounte...
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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...
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10/14/2022
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Designing feasible and effective architectures under diverse computation...
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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...
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07/14/2022
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
Detectingandsegmentingobjectswithinwholeslideimagesis essential in compu...
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06/23/2022
Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training
Graph instance contrastive learning has been proved as an effective task...
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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...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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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...
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03/31/2022
Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs
As a powerful tool for modeling complex relationships, hypergraphs are g...
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03/21/2022
Boost Test-Time Performance with Closed-Loop Inference
Conventional deep models predict a test sample with a single forward pro...
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03/12/2022
Equivariant Graph Mechanics Networks with Constraints
Learning to reason about relations and dynamics over multiple interactin...
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02/21/2022
Vision-Language Pre-Training with Triple Contrastive Learning
Vision-language representation learning largely benefits from image-text...
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02/17/2022
Transformer for Graphs: An Overview from Architecture Perspective
Recently, Transformer model, which has achieved great success in many ar...
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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...
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01/25/2022
Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction
Click-Through Rate (CTR) prediction, is an essential component of online...
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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...
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12/20/2021
RetroComposer: Discovering Novel Reactions by Composing Templates for Retrosynthesis Prediction
The main target of retrosynthesis is to recursively decompose desired mo...
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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...
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12/01/2021
Graph Convolutional Module for Temporal Action Localization in Videos
Temporal action localization has long been researched in computer vision...
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11/23/2021
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning
Labels are costly and sometimes unreliable. Noisy label learning, semi-s...
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09/08/2021
Local Augmentation for Graph Neural Networks
Data augmentation has been widely used in image data and linguistic data...
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08/12/2021
TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to transfer the knowledge lear...
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06/17/2021
Frustratingly Easy Transferability Estimation
Transferability estimation has been an essential tool in selecting a pre...
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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...
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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...
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05/29/2021
Learning Graphon Autoencoders for Generative Graph Modeling
Graphon is a nonparametric model that generates graphs with arbitrary si...
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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...
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05/23/2021
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Recent studies imply that deep neural networks are vulnerable to adversa...
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05/11/2021
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models
Accurate protein structure prediction from amino-acid sequences is criti...
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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...
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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...
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04/08/2021
QD-GCN: Query-Driven Graph Convolutional Networks for Attributed Community Search
Recently, attributed community search, a related but different problem t...
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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...
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03/20/2021
Recognizing Predictive Substructures with Subgraph Information Bottleneck
The emergence of Graph Convolutional Network (GCN) has greatly boosted t...
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03/17/2021
Diversified Multiscale Graph Learning with Graph Self-Correction
Though the multiscale graph learning techniques have enabled advanced fe...
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02/27/2021
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets
Designing feasible and effective architectures under diverse computation...
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02/20/2021
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Designing effective architectures is one of the key factors behind the s...
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02/03/2021
Learning Diverse-Structured Networks for Adversarial Robustness
In adversarial training (AT), the main focus has been the objective and ...
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01/22/2021
Towards Expectation-Maximization by SQL in RDBMS
Integrating machine learning techniques into RDBMSs is an important task...
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12/16/2020
Hierarchical Graph Capsule Network
Graph Neural Networks (GNNs) draw their strength from explicitly modelin...
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11/10/2020
Deep Multimodal Fusion by Channel Exchanging
Deep multimodal fusion by using multiple sources of data for classificat...
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11/04/2020
On Self-Distilling Graph Neural Network
Recently, the teacher-student knowledge distillation framework has demon...
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11/04/2020
RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
Retrosynthesis is the process of recursively decomposing target molecule...
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10/12/2020
Graph Information Bottleneck for Subgraph Recognition
Given the input graph and its label/property, several key problems of gr...
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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...
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09/15/2020
Microscope Based HER2 Scoring System
The overexpression of human epidermal growth factor receptor 2 (HER2) ha...
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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...
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08/22/2020
Tackling Over-Smoothing for General Graph Convolutional Networks
Increasing the depth of Graph Convolutional Networks (GCN), which in pri...
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07/28/2020