| 2026 | AAAI | Discovering Mixture Skills for Unsupervised Reinforcement Learning. | Nelson Ma, Junyu Xuan, Guangquan Zhang, Jie Lu |
| 2025 | AIED | Transfer Reinforcement Learning for Self-Regulated Learning Support: An Evaluation Using Successor Representations. | Kiyoshige Garcs, Gloria Milena Fernndez Nieto, Mladen Rakovic, Xinyu Li, Tongguang Li, Linxuan Zhao, Dragan Gasevic, Junyu Xuan, Hua Zuo |
| 2025 | AISTATS | Functional Stochastic Gradient MCMC for Bayesian Neural Networks. | Mengjing Wu, Junyu Xuan, Jie Lu |
| 2025 | ICLR | Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space. | Mengjing Wu, Junyu Xuan, Jie Lu |
| 2024 | IJCAI | Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning. | Wei Duan, Jie Lu, Junyu Xuan |
| 2024 | IJCAI | A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points. | Zihe Liu, Jie Lu, Guangquan Zhang, Junyu Xuan |
| 2024 | IJCNN | Decoupling Exploration and Exploitation for Unsupervised Pre-training with Successor Features. | Jaeyoon Kim, Junyu Xuan, Christy Jie Liang, Farookh Khadeer Hussain |
| 2024 | IJCNN | Improving the Factuality of Abstractive Text Summarization with Syntactic Structure-Aware Latent Semantic Space. | Jianbin Shen, Christy Jie Liang, Junyu Xuan |
| 2024 | UAI | Functional Wasserstein Bridge Inference for Bayesian Deep Learning. | Mengjing Wu, Junyu Xuan, Jie Lu |
| 2024 | UAI | Functional Wasserstein Variational Policy Optimization. | Junyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu |
| 2023 | EMNLP | Mitigating Intrinsic Named Entity-Related Hallucinations of Abstractive Text Summarization. | Jianbin Shen, Junyu Xuan, Christy Jie Liang |
| 2023 | IJCNN | An Autonomous Non-monolithic Agent with Multi-mode Exploration based on Options Framework. | Jaeyoon Kim, Junyu Xuan, Christy Jie Liang, Farookh Khadeer Hussain |
| 2023 | IJCNN | A Determinantal Point Process Based Novel Sampling Method of Abstractive Text Summarization. | Jianbin Shen, Junyu Xuan, Christy Jie Liang |
| 2022 | AAAI | Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples. | Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu |
| 2021 | ISKE | Negative Samples-enhanced Graph Convolutional Neural Networks. | Wei Duan, Junyu Xuan, Jie Lu |
| 2019 | ICDM | One-Stage Deep Instrumental Variable Method for Causal Inference from Observational Data. | Adi Lin, Jie Lu, Junyu Xuan, Fujin Zhu, Guangquan Zhang |
| 2018 | AAAI | Semantic Structure-Based Word Embedding by Incorporating Concept Convergence and Word Divergence. | Qian Liu, Heyan Huang, Guangquan Zhang, Yang Gao, Junyu Xuan, Jie Lu |
| 2015 | ICDM | Infinite Author Topic Model Based on Mixed Gamma-Negative Binomial Process. | Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo |
| 2014 | IJCNN | Extension of similarity measures in VSM: From orthogonal coordinate system to affine coordinate system. | Junyu Xuan, Jie Lu, Guangquan Zhang, Xiangfeng Luo |
| 2011 | DASC | Building Hierarchical Keyword Level Association Link Networks for Web Events Semantic Analysis. | Junyu Xuan, Xiangfeng Luo, Shunxiang Zhang, Zheng Xu, Huimin Liu, Feiyue Ye |