Shangqi Guo

According to our database, Shangqi Guo authored at least 24 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Chain-of-Detection: Enhancing Cross-Granularity Robotic Perception for Object Manipulation.

Tianrun Xu, Haichuan Gao, Changlin Chen, Yuxuan Li, Shiyuan Xu, Shangqi Guo, Feng Chen

IEEE Trans. Neural Networks Learn. Syst., April, 2026

HMEN: A hybrid modular network with dynamic expansion for continual learning.

Ziye Fang, Bo Wan, Shangqi Guo, Jian K. Liu

Knowl. Based Syst., 2026

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., March, 2025

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

Neurocomputing, 2025

Complete-Tree Space Favors Data-Efficient Link Prediction.

Chi Gao, Lukai Li, Yancheng Zhou, Shangqi Guo

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Hierarchical reinforcement learning from imperfect demonstrations through reachable coverage-based subgoal filtering.

Yu Tang, Shangqi Guo, Jinhui Liu, Bo Wan, Lingling An, Jian K. Liu

Knowl. Based Syst., 2024

2023

Partial Consistency for Stabilizing Undiscounted Reinforcement Learning.

Haichuan Gao, Zhile Yang, Tian Tan, Tianren Zhang, Jinsheng Ren, Pengfei Sun, Shangqi Guo, Feng Chen

IEEE Trans. Neural Networks Learn. Syst., December, 2023

PAC-Bayesian offline Meta-reinforcement learning.

Zheng Sun, Chenheng Jing, Shangqi Guo, Lingling An

Appl. Intell., November, 2023

Adjacency Constraint for Efficient Hierarchical Reinforcement Learning.

Tianren Zhang, Shangqi Guo, Tian Tan, Xiaolin Hu, Feng Chen

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Fast Counterfactual Inference for History-Based Reinforcement Learning.

Haichuan Gao, Tianren Zhang, Zhile Yang, Yuqing Guo, Jinsheng Ren, Shangqi Guo, Feng Chen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Orientation-Preserving Rewards' Balancing in Reinforcement Learning.

Jinsheng Ren, Shangqi Guo, Feng Chen

IEEE Trans. Neural Networks Learn. Syst., 2022

State-Temporal Compression in Reinforcement Learning With the Reward-Restricted Geodesic Metric.

Shangqi Guo, Qi Yan, Xin Su, Xiaolin Hu, Feng Chen

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Primitive-contrastive network: data-efficient self-supervised learning from robot demonstration videos.

Pengfei Sun, Zhile Yang, Tianren Zhang, Shangqi Guo, Feng Chen

Appl. Intell., 2022

Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks.

Zhile Yang, Shangqi Guo, Ying Fang, Jian K. Liu

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Subjective Learning for Open-Ended Data.

Tianren Zhang, Yizhou Jiang, Xin Su, Shangqi Guo, Feng Chen

CoRR, 2021

CRIL: Continual Robot Imitation Learning via Generative and Prediction Model.

Chongkai Gao, Haichuan Gao, Shangqi Guo, Tianren Zhang, Feng Chen

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020

Generative Memory for Lifelong Learning.

Xin Su, Shangqi Guo, Tian Tan, Feng Chen

IEEE Trans. Neural Networks Learn. Syst., 2020

Emergent Inference of Hidden Markov Models in Spiking Neural Networks Through Winner-Take-All.

Zhaofei Yu, Shangqi Guo, Fei Deng, Qi Yan, Keke Huang, Jian K. Liu, Feng Chen

IEEE Trans. Cybern., 2020

Cycle representation-disentangling network: learning to completely disentangle spatial-temporal features in video.

Pengfei Sun, Xin Su, Shangqi Guo, Feng Chen

Appl. Intell., 2020

Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning.

Tianren Zhang, Shangqi Guo, Tian Tan, Xiaolin Hu, Feng Chen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Task Understanding from Confusing Multi-task Data.

Xin Su, Yizhou Jiang, Shangqi Guo, Feng Chen

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Hierarchical Bayesian Inference and Learning in Spiking Neural Networks.

Shangqi Guo, Zhaofei Yu, Fei Deng, Xiaolin Hu, Feng Chen

IEEE Trans. Cybern., 2019

Subjectivity Learning Theory towards Artificial General Intelligence.

Xin Su, Shangqi Guo, Feng Chen

CoRR, 2019

Transferable Environment Model With Disentangled Dynamics.

Qi Yan, Shangqi Guo, Dagui Chen, Zhile Yang, Feng Chen

IEEE Access, 2019