Ruohan Wang
Ruohan Wang
University College London
Verified email at imperial.ac.uk - Homepage
Title
Cited by
Cited by
Year
Magan: Margin adaptation for generative adversarial networks
R Wang, A Cully, HJ Chang, Y Demiris
arXiv preprint arXiv:1704.03817, 2017
532017
Random expert distillation: Imitation learning via expert policy support estimation
R Wang, C Ciliberto, P Amadori, Y Demiris
International Conference on Machine Learning, 6536--6544, 2019
322019
Dynamic movement primitives plus: For enhanced reproduction quality and efficient trajectory modification using truncated kernels and local biases
R Wang, Y Wu, WL Chan, KP Tee
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
212016
Multi-modal robot apprenticeship: Imitation learning using linearly decayed dmp+ in a human-robot dialogue system
Y Wu, R Wang, LF D'Haro, RE Banchs, KP Tee
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
102018
Human-robot partnership: A study on collaborative storytelling
CJ Wong, YL Tay, R Wang, Y Wu
2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2016
102016
Real-time workload classification during driving using hypernetworks
R Wang, PV Amadori, Y Demiris
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
92018
Structured Prediction for Conditional Meta-Learning
R Wang, Y Demiris, C Ciliberto
2020 Conference on Neural Information Processing Systems, 2020
6*2020
Investigation on the roles of human and robot in collaborative storytelling
Y Wu, R Wang, YL Tay, CJ Wong
2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017
52017
Decision Anticipation for Driving Assistance Systems
PV Amadori, T Fischer, R Wang, Y Demiris
2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020
42020
Support-weighted Adversarial Imitation Learning
R Wang, C Ciliberto, P Amadori, Y Demiris
arXiv preprint arXiv:2002.08803, 2020
2020
Towards human-centered artificial intelligence: learning from demonstration and meta-learning for model adaptation
R Wang
PhD Thesis, 2020
2020
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Articles 1–11