Oleh Rybkin

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	总计	2019 年至今
引用	1111	1109
h 指数	12	12
i10 指数	12	12

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Kostas DaniilidisRuth Yalom Stone Professor of Computer and Information Science, University of Pennsylvania在 cis.upenn.edu 的电子邮件经过验证
Sergey LevineUC Berkeley, Physical Intelligence在 eecs.berkeley.edu 的电子邮件经过验证
Karl PertschUC Berkeley, Stanford University在 berkeley.edu 的电子邮件经过验证
Dinesh JayaramanAssistant Professor, University of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证
Chelsea FinnStanford University, Physical Intelligence在 cs.stanford.edu 的电子邮件经过验证
Deepak PathakAssistant Professor, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Danijar HafnerGoogle DeepMind在 google.com 的电子邮件经过验证
Konstantinos G. DerpanisYork University and Samsung AI Centre Toronto在 eecs.yorku.ca 的电子邮件经过验证
Andrew JaegleHead of AI, Captions在 nocapinc.com 的电子邮件经过验证
Karl SchmeckpeperThe AI Institute在 theaiinstitute.com 的电子邮件经过验证
Pieter AbbeelUC Berkeley | Covariant在 cs.berkeley.edu 的电子邮件经过验证
Ramanan SekarQualcomm在 qti.qualcomm.com 的电子邮件经过验证
Edward S. HuPhD Student, University of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证
Frederik EbertUC Berkeley在 berkeley.edu 的电子邮件经过验证
Joseph J. LimAssociate Professor at KAIST在 csail.mit.edu 的电子邮件经过验证
Russell MendoncaCarnegie Mellon University在 andrew.cmu.edu 的电子邮件经过验证
Annie XieGoogle DeepMind在 stanford.edu 的电子邮件经过验证
Igor MordatchGoogle DeepMind在 google.com 的电子邮件经过验证
Chuning ZhuUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Shenghao ZhouUniversity of Delaware在 udel.edu 的电子邮件经过验证

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Oleh Rybkin

其他姓名Oleg Rybkin

Postdoc, University of California, Berkeley

在 seas.upenn.edu 的电子邮件经过验证 - 首页

Reinforcement Learning Predictive Models Deep Learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	448	2020
Discovering and Achieving Goals with World Models R Mendonca, O Rybkin, K Daniilidis, D Hafner, D Pathak Neural Information Processing Systems (NeurIPS), 2021	129*	2021
Simple and Effective VAE Training with Calibrated Decoders O Rybkin, K Daniilidis, S Levine International Conference on Machine Learning (ICML), 2021	103	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	103	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	78	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	59	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	43	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	34*	2020
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	32*	2019
Planning goals for exploration ES Hu, R Chang, O Rybkin, D Jayaraman International Conference on Learning Representations (ICLR), 2023	27	2023
Metra: Scalable unsupervised rl with metric-aware abstraction S Park, O Rybkin, S Levine International Conference on Learning Representations (ICLR), 2024	25	2024
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	9	2022
Privileged Sensing Scaffolds Reinforcement Learning ES Hu, J Springer, O Rybkin, D Jayaraman The Twelfth International Conference on Learning Representations, 2024	3	2024
Predicting the future with transformational states A Jaegle, O Rybkin, KG Derpanis, K Daniilidis arXiv preprint arXiv:1803.09760, 2018	3	2018
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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