Thanard Kurutach

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Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
Aviv TamarTechnionVerified email at technion.ac.il
Ignasi ClaveraResearch Scientist, Covariant.aiVerified email at berkeley.edu
Yan DuanCovariant.AIVerified email at covariant.ai
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Kara LiuStanford UniversityVerified email at stanford.edu
Wilson YanPhD Student, UC BerkeleyVerified email at berkeley.edu
Yilin WuRobotics PhD at CMUVerified email at stanford.edu
Lerrel PintoNew York UniversityVerified email at cs.nyu.edu
Angelina WangStanford UniversityVerified email at stanford.edu
Deepak PathakAssistant Professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Michael (misha) LaskinStaff Research Scientist, DeepMindVerified email at google.com
Ajay JainUC BerkeleyVerified email at berkeley.edu
Tal DanielPostdoctoral Fellow, Carnegie Mellon University (CMU), USAVerified email at andrew.cmu.edu
Tomas Lozano-PerezProfessor of Computer Science, MITVerified email at mit.edu
Leslie KaelblingVerified email at csail.mit.edu
Lawson L.S. WongAssistant Professor, CCIS, Northeastern UniversityVerified email at ccs.neu.edu

Thanard Kurutach

Research Scientist, Cruise llc

Verified email at getcruise.com - Homepage

Reinforcement Learning Representation Learning Machine Learning Artificial Intelligence


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Model-ensemble trust-region policy optimization T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel arXiv preprint arXiv:1802.10592, 2018	567	2018
Mastering atari games with limited data W Ye, S Liu, T Kurutach, P Abbeel, Y Gao Advances in neural information processing systems 34, 25476-25488, 2021	255	2021
Learning to manipulate deformable objects without demonstrations Y Wu, W Yan, T Kurutach, L Pinto, P Abbeel arXiv preprint arXiv:1910.13439, 2019	225	2019
Learning plannable representations with causal infogan T Kurutach, A Tamar, G Yang, SJ Russell, P Abbeel Advances in Neural Information Processing Systems 31, 2018	218	2018
Learning robotic manipulation through visual planning and acting A Wang, T Kurutach, K Liu, P Abbeel, A Tamar arXiv preprint arXiv:1905.04411, 2019	159	2019
Sparse graphical memory for robust planning S Emmons, A Jain, M Laskin, T Kurutach, P Abbeel, D Pathak Advances in neural information processing systems 33, 5251-5262, 2020	56	2020
Hallucinative topological memory for zero-shot visual planning K Liu, T Kurutach, C Tung, P Abbeel, A Tamar International Conference on Machine Learning, 6259-6270, 2020	47	2020
Trajectory-wise multiple choice learning for dynamics generalization in reinforcement learning Y Seo, K Lee, I Clavera Gilaberte, T Kurutach, J Shin, P Abbeel Advances in Neural Information Processing Systems 33, 12968-12979, 2020	44	2020
Deep variational semi-supervised novelty detection T Daniel, T Kurutach, A Tamar arXiv preprint arXiv:1911.04971, 2019	30	2019
Object-based world modeling in semi-static environments with dependent Dirichlet-process mixtures LLS Wong, T Kurutach, LP Kaelbling, T Lozano-Pérez arXiv preprint arXiv:1512.00573, 2015	6	2015
Discrete Predictive Representation for Long-Horizon Planning T Kurutach, J Peng, Y Gao, S Russell, P Abbeel	1	2021
MAJOR-MINOR INTERSECTION PREDICTION USING TRAFFIC SIGN FEATURES T Kurutach, C Chen, O Jin US Patent US-20240246573-A1, 2024		2024
MULTIMODAL TRAJECTORY PREDICTIONS BASED ON GEOMETRIC ANCHORING A Abdulhamid, T Kurutach US Patent US-20240246574-A1, 2024		2024
AUTONOMOUS VEHICLE PREDICTION LAYER TRAINING T Kurutach, A Perez US Patent US-20240246537-A1, 2024		2024
HIERARCHICAL MODE ANCHORING T Kurutach, F Jiang, M Grecu US Patent US-20230192128-A1, 2023		2023
Learning, Planning, and Acting with Models T Kurutach University of California, Berkeley, 2021		2021
Object-based world modeling in semi-static environments with dependent dirichlet process mixtures LP Kaelbling, T Lozano-Pérez, T Kurutach		2016
MODEL-ENSEMBLE TRUST-REGION POLICY OPTI T Kurutach, I Clavera, Y Duan, A Tamar, P Abbeel

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