Transferable Environment Model With Disentangled Dynamics. - Qi Yan 005; Shangqi Guo; Dagui Chen; Zhile Yang; Feng Chen 007 (IEEE Access, 2019)

Subjectivity Learning Theory towards Artificial General Intelligence. - Xin Su; Shangqi Guo; Feng Chen 007 (CoRR, 2019)

Hierarchical Bayesian Inference and Learning in Spiking Neural Networks. - Shangqi Guo; Zhaofei Yu; Fei Deng 001; Xiaolin Hu 001; Feng Chen 007 (IEEE Trans. Cybern., 2019)

Task Understanding from Confusing Multi-task Data. - Xin Su; Yizhou Jiang; Shangqi Guo; Feng Chen 007 (ICML, 2020)

Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning. - Tianren Zhang; Shangqi Guo; Tian Tan 003; Xiaolin Hu 001; Feng Chen 007 (NeurIPS, 2020)

Cycle representation-disentangling network: learning to completely disentangle spatial-temporal features in video. - Pengfei Sun; Xin Su; Shangqi Guo; Feng Chen 007 (Appl. Intell., 2020)

Emergent Inference of Hidden Markov Models in Spiking Neural Networks Through Winner-Take-All. - Zhaofei Yu; Shangqi Guo; Fei Deng 001; Qi Yan 005; Keke Huang; Jian K. Liu; Feng Chen 007 (IEEE Trans. Cybern., 2020)

Generative Memory for Lifelong Learning. - Xin Su; Shangqi Guo; Tian Tan 003; Feng Chen 007 (IEEE Trans. Neural Networks Learn. Syst., 2020)

CRIL: Continual Robot Imitation Learning via Generative and Prediction Model. - Chongkai Gao; Haichuan Gao; Shangqi Guo; Tianren Zhang; Feng Chen 007 (IROS, 2021)

Subjective Learning for Open-Ended Data. - Tianren Zhang; Yizhou Jiang; Xin Su; Shangqi Guo; Feng Chen 007 (CoRR, 2021)

Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks. - Zhile Yang; Shangqi Guo; Ying Fang; Jian K. Liu (BMVC, 2022)

Primitive-contrastive network: data-efficient self-supervised learning from robot demonstration videos. - Pengfei Sun; Zhile Yang; Tianren Zhang; Shangqi Guo; Feng Chen 007 (Appl. Intell., 2022)

State-Temporal Compression in Reinforcement Learning With the Reward-Restricted Geodesic Metric. - Shangqi Guo; Qi Yan 005; Xin Su; Xiaolin Hu 001; Feng Chen 007 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Orientation-Preserving Rewards' Balancing in Reinforcement Learning. - Jinsheng Ren; Shangqi Guo; Feng Chen 007 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Fast Counterfactual Inference for History-Based Reinforcement Learning. - Haichuan Gao; Tianren Zhang; Zhile Yang; Yuqing Guo; Jinsheng Ren; Shangqi Guo; Feng Chen 007 (AAAI, 2023)

Adjacency Constraint for Efficient Hierarchical Reinforcement Learning. - Tianren Zhang; Shangqi Guo; Tian Tan 003; Xiaolin Hu 001; Feng Chen 007 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

PAC-Bayesian offline Meta-reinforcement learning. - Zheng Sun; Chenheng Jing; Shangqi Guo; Lingling An (Appl. Intell., 2023)

Partial Consistency for Stabilizing Undiscounted Reinforcement Learning. - Haichuan Gao; Zhile Yang; Tian Tan 003; Tianren Zhang; Jinsheng Ren; Pengfei Sun; Shangqi Guo; Feng Chen 007 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Hierarchical reinforcement learning from imperfect demonstrations through reachable coverage-based subgoal filtering. - Yu Tang 010; Shangqi Guo; Jinhui Liu; Bo Wan; Lingling An; Jian K. Liu (Knowl. Based Syst., 2024)

Causal dreamer for partially observable model-based reinforcement learning. - Haichuan Gao; Tianrun Xu; Tianren Zhang; Yuqing Guo; Chujie Zhao; Jinsheng Ren; Yizhou Jiang; Shangqi Guo; Feng Chen 007 (Neurocomputing, 2025)

Spiking Variational Policy Gradient for Brain Inspired Reinforcement Learning. - Zhile Yang; Shangqi Guo; Ying Fang; Zhaofei Yu; Jian K. Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)