Oleh Rybkin

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	すべて	2020 年以来
引用	1217	1203
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i10 指標	13	13

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Kostas DaniilidisRuth Yalom Stone Professor of Computer and Information Science, University of Pennsylvania確認したメールアドレス: cis.upenn.edu
Sergey LevineUC Berkeley, Physical Intelligence確認したメールアドレス: eecs.berkeley.edu
Karl PertschUC Berkeley, Stanford University確認したメールアドレス: berkeley.edu
Chelsea FinnStanford University, Physical Intelligence確認したメールアドレス: cs.stanford.edu
Pieter AbbeelUC Berkeley | Covariant確認したメールアドレス: cs.berkeley.edu
Dinesh JayaramanAssistant Professor, University of Pennsylvania確認したメールアドレス: seas.upenn.edu
Deepak PathakAssistant Professor, Carnegie Mellon University確認したメールアドレス: cs.cmu.edu
Danijar HafnerGoogle DeepMind確認したメールアドレス: google.com
Konstantinos G. DerpanisYork University and Samsung AI Centre Toronto確認したメールアドレス: eecs.yorku.ca
Andrew JaegleHead of AI, Captions確認したメールアドレス: nocapinc.com
Karl SchmeckpeperThe AI Institute確認したメールアドレス: theaiinstitute.com
Ramanan SekarQualcomm確認したメールアドレス: qti.qualcomm.com
Edward S. HuPhD Student, University of Pennsylvania確認したメールアドレス: seas.upenn.edu
Frederik EbertUC Berkeley確認したメールアドレス: berkeley.edu
Joseph J. LimAssociate Professor at KAIST確認したメールアドレス: csail.mit.edu
Russell MendoncaCarnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Annie XieGoogle DeepMind確認したメールアドレス: stanford.edu
Igor MordatchGoogle DeepMind, UC Berkeley確認したメールアドレス: google.com
Chuning ZhuUniversity of Washington確認したメールアドレス: cs.washington.edu
Seohong ParkUniversity of California, Berkeley確認したメールアドレス: berkeley.edu

フォロー

Oleh Rybkin

その他の名前Oleg Rybkin

Postdoc, University of California, Berkeley

確認したメールアドレス: eecs.berkeley.edu - ホームページ

Reinforcement Learning Scaling Laws World Models


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Planning to Explore via Self-Supervised World Models R Sekar, O Rybkin, K Daniilidis, P Abbeel, D Hafner, D Pathak International Conference on Machine Learning (ICML), 2020	482	2020
Discovering and Achieving Goals with World Models R Mendonca, O Rybkin, K Daniilidis, D Hafner, D Pathak Neural Information Processing Systems (NeurIPS), 2021	139*	2021
Simple and Effective VAE Training with Calibrated Decoders O Rybkin, K Daniilidis, S Levine International Conference on Machine Learning (ICML), 2021	116	2021
Reinforcement Learning with Videos: Combining Offline Observations with Interaction K Schmeckpeper, O Rybkin, K Daniilidis, S Levine, C Finn Conference on Robot Learning (CoRL), 2020	105	2020
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors K Pertsch, O Rybkin, F Ebert, C Finn, D Jayaraman, S Levine Neural Information Processing Systems (NeurIPS), 2020	86	2020
Learning Predictive Models From Observation and Interaction K Schmeckpeper, A Xie, O Rybkin, S Tian, K Daniilidis, S Levine, C Finn European Conference on Computer Vision (ECCV), 2020	60	2020
Model-Based Reinforcement Learning via Latent-Space Collocation O Rybkin, C Zhu, A Nagabandi, K Daniilidis, I Mordatch, S Levine International Conference on Machine Learning (ICML), 2021	53	2021
Keyframing the Future: Keyframe Discovery for Visual Prediction and Planning K Pertsch, O Rybkin, J Yang, S Zhou, K Derpanis, J Lim, K Daniilidis, ... Conference on Learning for Dynamics and Control (L4DC), 2020	38*	2020
Metra: Scalable unsupervised rl with metric-aware abstraction S Park, O Rybkin, S Levine International Conference on Learning Representations (ICLR), 2024	37	2024
Learning what you can do before doing anything O Rybkin, K Pertsch, KG Derpanis, K Daniilidis, A Jaegle International Conference on Learning representations (ICLR), 2019	34*	2019
Planning goals for exploration ES Hu, R Chang, O Rybkin, D Jayaraman International Conference on Learning Representations (ICLR), 2023	33	2023
Transferable Visual Control Policies Through Robot-Awareness ES Hu, K Huang, O Rybkin, D Jayaraman International Conference on Learning Representations (ICLR), 2022	15*	2022
Learning General World Models in a Handful of Reward-Free Deployments Y Xu, J Parker-Holder, A Pacchiano, P Ball, O Rybkin, S Roberts, ... Advances in Neural Information Processing Systems (NeurIPS) 35, 26820-26838, 2022	11	2022
Privileged Sensing Scaffolds Reinforcement Learning ES Hu, J Springer, O Rybkin, D Jayaraman The Twelfth International Conference on Learning Representations, 2024	5	2024
Predicting the future with transformational states A Jaegle, O Rybkin, KG Derpanis, K Daniilidis arXiv preprint arXiv:1803.09760, 2018	3	2018
Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos W Ye, F Liu, Z Ding, Y Gao, O Rybkin, P Abbeel arXiv preprint arXiv:2502.09886, 2025		2025
Value-Based Deep RL Scales Predictably O Rybkin, M Nauman, P Fu, C Snell, P Abbeel, S Levine, A Kumar arXiv preprint arXiv:2502.04327, 2025		2025
Learning to Act From Diverse Data Sources via World Models O Rybkin University of Pennsylvania, 2023		2023
Toward Continuous-Time Representations of Human Motion W Du, O Rybkin, L Zhang, J Shi ECCV Workshops, 2020		2020
Robust Focal Length Computation O Rybkin Czech Technical University in Prague, 2017		2017

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