Chelsea Finn

Citado por

	Todos	Desde 2017
Citações	24107	23715
Índice h	52	52
Índice i10	107	106

8000

4000

2000

6000

2016201720182019202020212022254 697 1674 3171 5313 7540 5259

Acesso público

Ver tudo

59 artigos

0 artigos

disponível

não disponível

Com base em autorizações de financiamento

Coautores

Sergey LevineUC Berkeley, GoogleEmail confirmado em eecs.berkeley.edu
Pieter AbbeelUC Berkeley | Covariant.AIEmail confirmado em cs.berkeley.edu
Tianhe YuStanford UniversityEmail confirmado em cs.stanford.edu
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyEmail confirmado em eecs.berkeley.edu
Karol HausmanGoogle Brain, StanfordEmail confirmado em google.com
Frederik EbertUC BerkeleyEmail confirmado em berkeley.edu
Mohammad BabaeizadehGoogle BrainEmail confirmado em google.com
Dumitru ErhanStaff Research Scientist, Google BrainEmail confirmado em google.com
Suraj NairStanford UniversityEmail confirmado em cs.stanford.edu
Annie XieStanford UniversityEmail confirmado em stanford.edu
Aravind RajeswaranFacebook AI Research (FAIR), UC BerkeleyEmail confirmado em cs.washington.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityEmail confirmado em cs.stanford.edu
Abhishek GuptaUniversity of California, BerkeleyEmail confirmado em berkeley.edu
Benjamin EysenbachCMU, GoogleEmail confirmado em google.com
Dinesh JayaramanAssistant Professor, University of PennsylvaniaEmail confirmado em seas.upenn.edu
Alex X. LeeResearch Scientist, DeepMindEmail confirmado em deepmind.com
Anusha NagabandiUC BerkeleyEmail confirmado em berkeley.edu
Coline DevinDeepMindEmail confirmado em deepmind.com
Sham M KakadeHarvard UniversityEmail confirmado em seas.harvard.edu
Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityEmail confirmado em princeton.edu

Seguir

Chelsea Finn

Stanford University, Google

Email confirmado em cs.stanford.edu - Página inicial

machine learning robotics reinforcement learning


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Model-agnostic meta-learning for fast adaptation of deep networks C Finn, P Abbeel, S Levine International Conference on Machine Learning (ICML), 1126-1135, 2017	6730	2017
End-to-end training of deep visuomotor policies S Levine, C Finn, T Darrell, P Abbeel Journal of Machine Learning Research 17 (1), 1334-1373, 2016	2990	2016
Unsupervised learning for physical interaction through video prediction C Finn, I Goodfellow, S Levine Advances in neural information processing systems 29, 2016	948	2016
Guided cost learning: Deep inverse optimal control via policy optimization C Finn, S Levine, P Abbeel International Conference on Machine Learning (ICML), 49-58, 2016	785	2016
Deep visual foresight for planning robot motion C Finn, S Levine 2017 IEEE International Conference on Robotics and Automation (ICRA), 2786-2793, 2017	629	2017
Probabilistic model-agnostic meta-learning C Finn, K Xu, S Levine Neural Information Processing Systems (NeurIPS), 2018	552	2018
Deep spatial autoencoders for visuomotor learning C Finn, XY Tan, Y Duan, T Darrell, S Levine, P Abbeel 2016 IEEE International Conference on Robotics and Automation (ICRA), 512-519, 2016	547*	2016
Model-based reinforcement learning for atari L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ... International Conference on Learning Representations (ICLR), 2020	503	2020
One-shot visual imitation learning via meta-learning C Finn, T Yu, T Zhang, P Abbeel, S Levine Conference on Robot Learning (CoRL), 2017	430	2017
Meta-learning with implicit gradients A Rajeswaran, C Finn, S Kakade, S Levine Neural Information Processing Systems (NeurIPS), 2019	429	2019
Recasting gradient-based meta-learning as hierarchical bayes E Grant, C Finn, S Levine, T Darrell, T Griffiths International Conference on Learning Representations (ICLR), 2018	420	2018
Learning to adapt in dynamic, real-world environments through meta-reinforcement learning A Nagabandi, I Clavera, S Liu, RS Fearing, P Abbeel, S Levine, C Finn International Conference on Learning Representations (ICLR), 2019	416*	2019
Stochastic variational video prediction M Babaeizadeh, C Finn, D Erhan, RH Campbell, S Levine International Conference on Learning Representations (ICLR), 2017	401	2017
Wilds: A benchmark of in-the-wild distribution shifts PW Koh, S Sagawa, H Marklund, SM Xie, M Zhang, A Balsubramani, ... International Conference on Machine Learning (ICML), 5637-5664, 2021	346	2021
Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning T Yu, D Quillen, Z He, R Julian, K Hausman, C Finn, S Levine Conference on Robot Learning (CoRL), 2019	346	2019
Efficient off-policy meta-reinforcement learning via probabilistic context variables K Rakelly, A Zhou, D Quillen, C Finn, S Levine International Conference on Machine Learning (ICML), 2019	345	2019
Stochastic adversarial video prediction AX Lee, R Zhang, F Ebert, P Abbeel, C Finn, S Levine arXiv preprint arXiv:1804.01523, 2018	335	2018
Online meta-learning C Finn, A Rajeswaran, S Kakade, S Levine International Conference on Machine Learning (ICML), 2019	298	2019
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	296	2021
A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models C Finn, P Christiano, P Abbeel, S Levine NeurIPS Workshop on Adversarial Training, 2016	284	2016

O sistema não pode efectuar a operação agora. Tente novamente mais tarde.

Artigos 1–20

Citações por ano

Citações duplicadas

Citações unidas

Adicionar coautoresCoautores

Seguir

Citado por

Coautores