Следене
Zihan Ding
Zihan Ding
Потвърден имейл адрес: princeton.edu - Начална страница
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Позовавания
Позовавания
Година
Deep Reinforcement Learning: Fundamentals, Research and Applications
H Dong, Z Ding, S Zhang
Springer Nature, 2020
249*2020
Introduction to reinforcement learning
Z Ding, Y Huang, H Yuan, H Dong
Deep reinforcement learning: fundamentals, research and applications, 47-123, 2020
1042020
Challenges of reinforcement learning
Z Ding, H Dong
Deep Reinforcement Learning: Fundamentals, Research and Applications, 249-272, 2020
622020
Deep reinforcement learning for intelligent transportation systems
XY Liu, Z Ding, S Borst, A Walid
NIPS Workshop on Machine Learning for Intelligent Transportation Systems 2018, 2018
442018
Sim-to-Real Transfer for Optical Tactile Sensing
Z Ding, NF Lepora, E Johns
International Conference on Robotics and Automation (ICRA 2020), 2020
432020
Crossing the gap: A deep dive into zero-shot sim-to-real transfer for dynamics
E Valassakis, Z Ding, E Johns
International Conference on Intelligent Robots and Systems (IROS 2020), 2020
332020
Tensor Super-Resolution with Generative Adversarial Nets: A Large Image Generation Approach
Z Ding, XY Liu, M Yin, L Kong
IJCAI 2019 International Workshop on Human Brain and Artificial Intelligence …, 2019
31*2019
Arena: A general evaluation platform and building toolkit for multi-agent intelligence
Y Song, A Wojcicki, T Lukasiewicz, J Wang, A Aryan, Z Xu, M Xu, Z Ding, ...
Proceedings of the AAAI conference on artificial intelligence 34 (05), 7253-7260, 2020
302020
Cdt: Cascading decision trees for explainable reinforcement learning
Z Ding, P Hernandez-Leal, GW Ding, C Li, R Huang
arXiv preprint arXiv:2011.07553, 2020
262020
Droid: Minimizing the reality gap using single-shot human demonstration
YY Tsai, H Xu, Z Ding, C Zhang, E Johns, B Huang
IEEE Robotics and Automation Letters 6 (2), 3168-3175, 2021
222021
Fast high-fidelity readout of a single trapped-ion qubit via machine-learning methods
ZH Ding, JM Cui, YF Huang, CF Li, T Tu, GC Guo
Physical Review Applied 12 (1), 014038, 2019
222019
Sim-to-real transfer for robotic manipulation with tactile sensory
Z Ding, YY Tsai, WW Lee, B Huang
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021
162021
Probabilistic mixture-of-experts for efficient deep reinforcement learning
J Ren, Y Li, Z Ding, W Pan, H Dong
arXiv preprint arXiv:2104.09122, 2021
142021
Rlzoo: A comprehensive and adaptive reinforcement learning library
Z Ding, T Yu, Y Huang, H Zhang, L Mai, H Dong
arXiv preprint arXiv:2009.08644, 1, 2020
11*2020
Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning
Z Ding, C Jin
arXiv preprint arXiv:2309.16984, 2023
72023
Learning a universal human prior for dexterous manipulation from human preference
Z Ding, Y Chen, AZ Ren, SS Gu, Q Wang, H Dong, C Jin
arXiv preprint arXiv:2304.04602, 2023
72023
Multi-agent reinforcement learning for network load balancing in data center
Z Yao, Z Ding, T Clausen
Proceedings of the 31st ACM International Conference on Information …, 2022
72022
Reinforced workload distribution fairness
Z Yao, Z Ding, TH Clausen
5th Workshop on Machine Learning for Systems at 35th Conference on Neural …, 2021
62021
Accelerated exhaustive eye glints localization method for infrared video oculography
Z Ding, J Luo, H Deng
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 620-627, 2018
52018
Diffusion World Model
Z Ding, A Zhang, Y Tian, Q Zheng
arXiv preprint arXiv:2402.03570, 2024
42024
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