| Harnessing Reinforcement Learning for Neural Motion Planning T Jurgenson, A Tamar Robotics: Science and Systems 2019, 2019 | 62 | 2019 |
| Sub-Goal Trees – a Framework for Goal-Based Reinforcement Learning T Jurgenson, O Avner, E Groshev, A Tamar International Conference on Machine Learning (ICML) 2020, 2020 | 36 | 2020 |
| Sub-Goal Trees--a Framework for Goal-Directed Trajectory Prediction and Optimization T Jurgenson, E Groshev, A Tamar arXiv preprint arXiv:1906.05329, 2019 | 12 | 2019 |
| Goal-Conditioned Supervised Learning with Sub-Goal Prediction T Jurgenson, A Tamar arXiv preprint arXiv:2305.10171, 2023 | 2 | 2023 |
| Learning decision trees with stochastic linear classifiers T Jurgenson, Y Mansour Algorithmic Learning Theory, 489-528, 2018 | 2 | 2018 |
| MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning Z Rimon, T Jurgenson, O Krupnik, G Adler, A Tamar arXiv preprint arXiv:2403.09859, 2024 | 1 | 2024 |
| Fine-Tuning Generative Models as an Inference Method for Robotic Tasks O Krupnik, E Shafer, T Jurgenson, A Tamar Conference on Robot Learning, 866-886, 2023 | | 2023 |
| Hierarchical Planning for Rope Manipulation using Knot Theory and a Learned Inverse Model M Sudry, T Jurgenson, A Tamar, E Karpas Conference on Robot Learning, 1596-1609, 2023 | | 2023 |
| Hierarchical Planning for Rope Manipulation using Knot Theory and a Learned Inverse Model M Sudry, T Jurgenson, A Tamar, E Karpas 7th Annual Conference on Robot Learning, 2023 | | 2023 |
Aviv TamarTechnionVerified email at technion.ac.il
