| Imitating Latent Policies from Observation AD Edwards, H Sahni, Y Schroecker, CL Isbell International Conference on Machine Learning, 2018 | 50 | 2018 |
| Generative predecessor models for sample-efficient imitation learning Y Schroecker, M Vecerik, J Scholz International Conference on Learning Representations, 2019 | 18 | 2019 |
| State aware imitation learning Y Schroecker, C Isbell Proceedings of the 31st International Conference on Neural Information …, 2017 | 16 | 2017 |
| Directing policy search with interactively taught via-points Y Schroecker, H Ben Amor, A Thomaz International Conference on Autonomous Agents & Multiagent Systems, 1052-1059, 2016 | 10 | 2016 |
| Active learning within constrained environments through imitation of an expert questioner K Bullard, Y Schroecker, S Chernova International Joint Conference on Artificial Intelligence, 2019 | 9 | 2019 |
| Universal value density estimation for imitation learning and goal-conditioned reinforcement learning Y Schroecker, C Isbell arXiv preprint arXiv:2002.06473, 2020 | 2 | 2020 |
| Imitation learning using a generative predecessor neural network M Vecerik, Y Schroecker, JK Scholz US Patent 10,872,294, 2020 | | 2020 |
| Manipulating State Space Distributions for Sample-Efficient Imitation-Learning YKD Schroecker Georgia Institute of Technology, 2020 | | 2020 |
| Imitating latent policies from observation Download PDF A Edwards, H Sahni, Y Schroecker, C Isbell | | |
