419 citations · 932 across the 46 of their papers we have counts for
6 papers · 1 filter
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis
Bingzhe Wu, Zhicong Liang, Yatao Bian +3
Recently, generalization bounds of the non-convex empirical risk minimization paradigm using Stochastic Gradient Langevin Dynamics (SGLD) have been extensively studied. Several the…
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne +4
Protein complex formation is a central problem in biology, being involved in most of the cell's processes, and essential for applications, e.g. drug design or protein engineering.…
-Laplacian Based Graph Neural Networks
Guoji Fu, Peilin Zhao, Yatao Bian
Graph neural networks (GNNs) have demonstrated superior performance for semi-supervised node classification on graphs, as a result of their ability to exploit node features and top…
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
Yatao Bian, Yu Rong, Tingyang Xu +3
Valuation problems, such as feature interpretation, data valuation and model valuation for ensembles, become increasingly more important in many machine learning applications. Such…
Recognizing Predictive Substructures with Subgraph Information Bottleneck
Junchi Yu, Tingyang Xu, Yu Rong +3
The emergence of Graph Convolutional Network (GCN) has greatly boosted the progress of graph learning. However, two disturbing factors, noise and redundancy in graph data, and lack…
Diversified Multiscale Graph Learning with Graph Self-Correction
Yuzhao Chen, Yatao Bian, Jiying Zhang +4
Though the multiscale graph learning techniques have enabled advanced feature extraction frameworks, the classic ensemble strategy may show inferior performance while encountering…