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Zichuan Liu
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Year
Spatial-temporal conv-sequence learning with accident encoding for traffic flow prediction
Z Liu, R Zhang, C Wang, Z Xiao, H Jiang
IEEE Transactions on Network Science and Engineering 9 (3), 1765-1775, 2022
142022
Multi-view spatial-temporal model for travel time estimation
Z Liu, Z Wu, M Wang, R Zhang
SIGSPATIAL 2021, 2021
52021
N Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning
Z Liu, Y Zhu, C Chen
ICML 2023, 2023
42023
MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees
Z Liu, Y Zhu, Z Wang, Y Gao, C Chen
arXiv preprint arXiv:2209.07225, 2022
32022
RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models
Z Wang, Z Liu, Y Zhang, A Zhong, L Fan, L Wu, Q Wen
arXiv preprint arXiv:2310.16340, 2023
22023
Boosting Value Decomposition via Unit-Wise Attentive State Representation for Cooperative Multi-Agent Reinforcement Learning
Q Zhao, Y Zhu, Z Liu, Z Wang, C Chen
arXiv preprint arXiv:2305.07182, 2023
12023
Protecting Your LLMs with Information Bottleneck
Z Liu, Z Wang, L Xu, J Wang, L Song, T Wang, C Chen, W Cheng, J Bian
arXiv preprint arXiv:2404.13968, 2024
2024
Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning
L Xu, Z Liu, A Dockhorn, D Perez-Liebana, J Wang, L Song, J Bian
IEEE CoG 2024, 2024
2024
Explaining Time Series via Contrastive and Locally Sparse Perturbations
Z Liu, Y Zhang, T Wang, Z Wang, D Luo, M Du, M Wu, Y Wang, C Chen, ...
ICLR 2024, 2024
2024
Position Paper: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
ICML, 2024
2024
TimeX++: Learning Time-Series Explanations with Information Bottleneck
ICML, 2024
2024
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