Evan Zheran Liu 个人学术档案

引用次数

	总计	2019 年至今
引用	1117	1062
h 指数	9	9
i10 指数	9	9

360

180

270

2017201820192020202120222023202413 41 42 57 115 221 355 272

开放获取的出版物数量

查看全部

6 篇文章

0 篇文章

可查看的文章

无法查看的文章

根据资助方的强制性开放获取政策

合著作者

Percy LiangAssociate Professor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
Chelsea FinnStanford University, Google在 cs.stanford.edu 的电子邮件经过验证
Panupong PasupatGoogle在 cs.stanford.edu 的电子邮件经过验证
Kelvin GuuSenior Staff Research Scientist, Google在 google.com 的电子邮件经过验证
Aditi RaghunathanAssistant professor, Carnegie Mellon University在 cmu.edu 的电子邮件经过验证
Pang Wei KohUniversity of Washington在 cs.washington.edu 的电子邮件经过验证
Shiori SagawaPhD Student, Stanford University在 stanford.edu 的电子邮件经过验证
Annie S. ChenStanford University在 stanford.edu 的电子邮件经过验证
Emma BrunskillAssociate Professor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
Milad HashemiGoogle在 google.com 的电子邮件经过验证
Tim (Tianlin) ShiPhD Student at Stanford University在 stanford.edu 的电子邮件经过验证
Luisa ZintgrafDeepMind在 deepmind.com 的电子邮件经过验证
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, Waymo在 cs.ox.ac.uk 的电子邮件经过验证
Junwhan AhnGoogle DeepMind在 google.com 的电子邮件经过验证
Kevin SwerskyGoogle Brain在 cs.toronto.edu 的电子邮件经过验证
Parthasarathy RanganathanGoogle在 google.com 的电子邮件经过验证
Ramtin KeramatiStanford University在 stanford.edu 的电子邮件经过验证
Chris PiechAssistant Professor, Stanford University在 cs.stanford.edu 的电子邮件经过验证
Yiding JiangPhD Student, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Benjamin EysenbachPrinceton University在 princeton.edu 的电子邮件经过验证

关注

Evan Zheran Liu

Stanford University, Imbue

在 cs.stanford.edu 的电子邮件经过验证 - 首页

Reinforcement Learning Machine Learning 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
Just train twice: Improving group robustness without training group information EZ Liu, B Haghgoo, AS Chen, A Raghunathan, PW Koh, S Sagawa, ... International Conference on Machine Learning, 6781-6792, 2021	432	2021
From language to programs: Bridging reinforcement learning and maximum marginal likelihood K Guu, P Pasupat, EZ Liu, P Liang Association for Computational Linguistics (ACL), 2017	204	2017
Reinforcement learning on web interfaces using workflow-guided exploration EZ Liu, K Guu, P Pasupat, T Shi, P Liang International Conference on Learning Representations (ICLR), 2018	136	2018
A survey of meta-reinforcement learning J Beck, R Vuorio, EZ Liu, Z Xiong, L Zintgraf, C Finn, S Whiteson arXiv preprint arXiv:2301.08028, 2023	106	2023
An imitation learning approach for cache replacement E Liu, M Hashemi, K Swersky, P Ranganathan, J Ahn International Conference on Machine Learning, 6237-6247, 2020	85	2020
Decoupling exploration and exploitation for meta-reinforcement learning without sacrifices EZ Liu, A Raghunathan, P Liang, C Finn International conference on machine learning, 6925-6935, 2021	75	2021
Mapping natural language commands to web elements P Pasupat, TS Jiang, EZ Liu, K Guu, P Liang Empirical Methods in Natural Language Processing (EMNLP), 2018	44	2018
Learning Options via Compression Y Jiang, EZ Liu, B Eysenbach, Z Kolter, C Finn Neural Information Processing Systems (NeurIPS), 2022	11	2022
Giving Feedback on Interactive Student Programs with Meta-Exploration EZ Liu, M Stephan, A Nie, C Piech, E Brunskill, C Finn Neural Information Processing Systems (NeurIPS), 2022	10	2022
Learning abstract models for strategic exploration and fast reward transfer EZ Liu, R Keramati, S Seshadri, K Guu, P Pasupat, E Brunskill, P Liang arXiv preprint arXiv:2007.05896, 2020	8*	2020
Simple embodied language learning as a byproduct of meta-reinforcement learning EZ Liu, S Suri, T Mu, A Zhou, C Finn International Conference on Machine Learning, 21997-22008, 2023	3	2023
Analyzing a caching model L Sixt, EZ Liu, M Pellat, J Wexler, M Hashemi, B Kim, M Maas arXiv preprint arXiv:2112.06989, 2021	2	2021
Meta-Reinforcement Learning: Algorithms and Applications EZ Liu Stanford University, 2023	1	2023
AutoBencher: Creating Salient, Novel, Difficult Datasets for Language Models XL Li, EZ Liu, P Liang, T Hashimoto arXiv preprint arXiv:2407.08351, 2024		2024
A Fast and Accurate Machine Learning Autograder for the Breakout Assignment EZ Liu, D Yuan, A Ahmed, E Cornwall, J Woodrow, K Burns, A Nie, ... Proceedings of the 55th ACM Technical Symposium on Computer Science …, 2024		2024
Learning to Explore in POMDPs with Informational Rewards A Xie, LM Bhamidipaty, EZ Liu, J Hong, S Levine, C Finn Forty-first International Conference on Machine Learning, 0

系统目前无法执行此操作，请稍后再试。

文章 1–16

每年引用数

重复的引用

合并的引用

添加合著者合著作者

上传 PDF

关注此作者

引用次数

合著作者

引用