Cowen-Rivers, A.; Lyu, W.; Tutunov, R.; Wang, Z.; Grosnit, A.; Griffiths, R.R.; Maraval, A.; Jianye, H.; Wang, J.; Peters, J.; Bou Ammar, H. (2022). HEBO: An Empirical Study of Assumptions in Bayesian Optimisation, Journal of Artificial Intelligence Research, 74, pp.1269-1349.
BibTeX Reference Wang, Z. (2018). Representation Learning for Tactile Manipulation, Master Thesis. Download Article BibTeX Reference Wang, Z.; Boularias, A.; Muelling, K.; Schoelkopf, B.; Peters, J. (2017). Anticipatory Action Selection for Human-Robot Table Tennis, Artificial Intelligence, 247, pp.399-414. Download Article BibTeX Reference Zhang, K.; Wang, Z.; Zhang, J.; Schoelkopf, B. (2014). On estimation of functional causal models: General results and application to post-nonlinear causal model, ACM Transactions on Intelligent Systems and Technologies. BibTeX Reference Wang, Z.; Muelling, K.; Deisenroth, M. P.; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2013). Probabilistic Movement Modeling for Intention Inference in Human-Robot Interaction, International Journal of Robotics Research (IJRR), 32, 7, pp.841-858. Download Article BibTeX Reference Zhang, K; Schölkopf, B.; Muandet, K.; Wang, Z. (2013). Domain adaptation under Target and Conditional Shift, Proceedings of the 30th International Conference on Machine Learning (ICML). Download Article BibTeX Reference Wang, Z. (2013). Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Model, PhD Thesis. Download Article BibTeX Reference Wang, Z.;Deisenroth, M; Ben Amor, H.; Vogt, D.; Schoelkopf, B.; Peters, J. (2012). Probabilistic Modeling of Human Movements for Intention Inference, Proceedings of Robotics: Science and Systems (R:SS). Download Article BibTeX Reference Wang, Z.; Lampert, C; Muelling, K; Schoelkopf, B.; Peters, J. (2011). Learning Anticipation Policies for Robot Table Tennis, IEEE/RSJ International Conference on Intelligent Robot Systems (IROS). Download Article BibTeX Reference Wang, Z.; Boularias, A.; Muelling, K.; Peters, J. (2011). Balancing Safety and Exploitability in Opponent Modeling, Proceedings of the Twenty-Fifth National Conference on Artificial Intelligence (AAAI). Download Article BibTeX Reference |