Publications

You can also find my articles on my Google Scholar profile.

Published

Dynamical modulation of hippocampal replay through firing rate adaptation
Zilong Ji, Tianhao Chu, Xingsi Dong, Changmin Yu, Daniel Bush, Neil Burgess & Si Wu
Nature Communications, 2026
Discovering temporally compositional neural manifolds with switching infinite GPFA
Changmin Yu, Maneesh Sahani, Máté Lengyel
International Conference on Learning Representations (ICLR), 2025 Spotlight
Successor-predecessor intrinsic exploration
Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J. Gershman
Advances in Neural Information Processing Systems (NeurIPS), 2023
Unsupervised representation learning with recognition-parametrised probabilistic models
William Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Structured recognition for generative models with explaining away
Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani
Advances in Neural Information Processing Systems (NeurIPS), 2022
Learning state representations via retracing in reinforcement learning
Changmin Yu, Dong Li, Jianye Hao, Jun Wang, Neil Burgess
International Conference on Learning Representations (ICLR), 2021
What about inputting policy in value function: policy representation and policy-extended value function approximator
Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang
AAAI Conference on Artificial Intelligence, 2020 Long Presentation
Prediction and generalisation over directed actions by grid cells
Changmin Yu, Timothy E.J. Behrens, Neil Burgess
International Conference on Learning Representations (ICLR), 2020
Deep kernel learning approach to engine emissions modeling
Changmin Yu, Marko Seslija, George Brownbridge, Sebastian Mosbach, Markus Kraft, Mohammad Parsi, Mark Davis, Vivian Page, Amit Bhave
Data-Centric Engineering, 2020

Preprints

Hierarchical successor representation for robust transfer
Changmin Yu, Máté Lengyel
Under Review, 2026
Hippocampal theta sweeps indicate goal direction
Changmin Yu, Zilong Ji, Jake Ormond, John O'Keefe, Neil Burgess
Under Review, 2025
SEREN: knowing when to explore and when to exploit
Changmin Yu, David Mguni, Dong Li, Aivar Sootla, Jun Wang, Neil Burgess
arXiv preprint, 2022
DESTA: a framework for safe reinforcement learning with Markov games of intervention
David Henry Mguni, Usman Islam, Yaqi Sun, Xiuling Zhang, Joel Jennings, Aivar Sootla, Changmin Yu, Jun Wang, Yaodong Yang
arXiv preprint, 2021

Conference Workshops

Leveraging episodic memory to improve world models for reinforcement learning
Julian Coda-Forno, Changmin Yu, Qinghai Guo, Zafeirios Fountas, Neil Burgess
Memory in Artificial and Real Intelligence Workshop at NeurIPS, 2022
Learning state representations via temporal cycle-consistency constraint in Mmodel-based reinforcement learning
Changmin Yu, Dong Li, Hangyu Mao, Jianye Hao, Neil Burgess
Self-Supervision for Reinforcement Learning Workshop at ICLR, 2021

PhD Thesis

Hippocampus-inspired representation learning for artificial agents
Changmin Yu
PhD Thesis, UCL. Examiners: Peter Dayan, Andrew Saxe