Xuan, Junyu

13 publications

NeurIPS 2025 Bayesian Ego-Graph Inference for Networked Multi-Agent Reinforcement Learning Wei Duan, Jie Lu, Junyu Xuan

ICLR 2025 Bridging the Gap Between Variational Inference and Stochastic Gradient MCMC in Function Space Mengjing Wu, Junyu Xuan, Jie Lu

AISTATS 2025 Functional Stochastic Gradient MCMC for Bayesian Neural Networks Mengjing Wu, Junyu Xuan, Jie Lu

IJCAI 2024 A Behavior-Aware Approach for Deep Reinforcement Learning in Non-Stationary Environments Without Known Change Points Zihe Liu, Jie Lu, Guangquan Zhang, Junyu Xuan

UAI 2024 Functional Wasserstein Bridge Inference for Bayesian Deep Learning Mengjing Wu, Junyu Xuan, Jie Lu

UAI 2024 Functional Wasserstein Variational Policy Optimization Junyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu

IJCAI 2024 Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning Wei Duan, Jie Lu, Junyu Xuan

TMLR 2024 Layer-Diverse Negative Sampling for Graph Neural Networks Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan

MLJ 2023 DAFS: A Domain Aware Few Shot Generative Model for Event Detection Nan Xia, Hang Yu, Yin Wang, Junyu Xuan, Xiangfeng Luo

AAAI 2022 Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu

NeurIPS 2020 Path Integral Based Convolution and Pooling for Graph Neural Networks Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò

AAAI 2018 Semantic Structure-Based Word Embedding by Incorporating Concept Convergence and Word Divergence Qian Liu, Heyan Huang, Guangquan Zhang, Yang Gao, Junyu Xuan, Jie Lu

MLJ 2017 A Bayesian Nonparametric Model for Multi-Label Learning Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo