Goal-conditioned imitation learning Y Ding, C Florensa, P Abbeel, M Phielipp Advances in neural information processing systems 32, 2019 | 229 | 2019 |
Language-conditioned imitation learning for robot manipulation tasks S Stepputtis, J Campbell, M Phielipp, S Lee, C Baral, H Ben Amor Advances in Neural Information Processing Systems 33, 13139-13150, 2020 | 138 | 2020 |
Motion2vec: Semi-supervised representation learning from surgical videos AK Tanwani, P Sermanet, A Yan, R Anand, M Phielipp, K Goldberg 2020 IEEE International Conference on Robotics and Automation (ICRA), 2174-2181, 2020 | 43 | 2020 |
Shrouds: Optimal separating surfaces for enumerated volumes GM Nielson, G Graf, R Holmes, A Huang, M Phielipp VisSym 3, 75-84, 2003 | 24 | 2003 |
Group selfies: a robust fragment-based molecular string representation AH Cheng, A Cai, S Miret, G Malkomes, M Phielipp, A Aspuru-Guzik Digital Discovery 2 (3), 748-758, 2023 | 22 | 2023 |
Clone swarms: Learning to predict and control multi-robot systems by imitation S Zhou, MJ Phielipp, JA Sefair, SI Walker, HB Amor 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 19 | 2019 |
Anymorph: Learning transferable polices by inferring agent morphology B Trabucco, M Phielipp, G Berseth International Conference on Machine Learning, 21677-21691, 2022 | 17 | 2022 |
Hierarchical policy learning is sensitive to goal space design Z Dwiel, M Candadai, M Phielipp, AK Bansal arXiv preprint arXiv:1905.01537, 2019 | 15 | 2019 |
User interface with software lensing for very long lists of content RR Dunton, MJ Phielipp US Patent 9,024,864, 2015 | 15 | 2015 |
Instance-based generalization in reinforcement learning M Bertran, N Martinez, M Phielipp, G Sapiro Advances in Neural Information Processing Systems 33, 11333-11344, 2020 | 14 | 2020 |
Maximizing ensemble diversity in deep reinforcement learning H Sheikh, M Phielipp, L Boloni International Conference on Learning Representations, 2021 | 13 | 2021 |
Method of determining profiles for widget channel viewers MJ Phielipp US Patent 8,635,638, 2014 | 13 | 2014 |
Modularity through attention: Efficient training and transfer of language-conditioned policies for robot manipulation Y Zhou, S Sonawani, M Phielipp, S Stepputtis, HB Amor arXiv preprint arXiv:2212.04573, 2022 | 12 | 2022 |
Learning intrinsic symbolic rewards in reinforcement learning HU Sheikh, S Khadka, S Miret, S Majumdar, M Phielipp 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 12 | 2022 |
Dialogue system with audio watermark MJ Phielipp US Patent 9,818,414, 2017 | 11 | 2017 |
Pretraining graph neural networks for few-shot analog circuit modeling and design K Hakhamaneshi, M Nassar, M Phielipp, P Abbeel, V Stojanovic IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022 | 10 | 2022 |
Analytically directed data collection in sensor network RL Vaughn, SS Cheema, MD Savoy, MJ Phielipp, S Sindia US Patent App. 15/201,377, 2018 | 8 | 2018 |
Minimizing communication while maximizing performance in multi-agent reinforcement learning VK Vijay, H Sheikh, S Majumdar, M Phielipp arXiv preprint arXiv:2106.08482, 2021 | 7 | 2021 |
Learning modular language-conditioned robot policies through attention Y Zhou, S Sonawani, M Phielipp, H Ben Amor, S Stepputtis Autonomous Robots 47 (8), 1013-1033, 2023 | 6 | 2023 |
DNS: Determinantal point process based neural network sampler for ensemble reinforcement learning H Sheikh, K Frisbee, M Phielipp International Conference on Machine Learning, 19731-19746, 2022 | 6 | 2022 |