Neev Parikh 个人学术档案 - 学术资源搜索

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George KonidarisBrown在 cs.brown.edu 的电子邮件经过验证
Kavosh AsadiResearch Scientist, Amazon在 amazon.com 的电子邮件经过验证
Michael LittmanBrown University在 brown.edu 的电子邮件经过验证
Ronald ParrProfessor of Computer Science, Duke University在 cs.duke.edu 的电子邮件经过验证
Cameron S. AllenPostdoc, UC Berkeley在 berkeley.edu 的电子邮件经过验证
Omer GottesmanAmazon在 amazon.com 的电子邮件经过验证
Max MerlinBrown University在 brown.edu 的电子邮件经过验证
Scott FrickelBrown University在 brown.edu 的电子邮件经过验证
Thomas Marlow, Ph.D.Texas A&M University, Department of Sociology在 tamu.edu 的电子邮件经过验证
Naveen SrinivasanBrown University在 alumni.brown.edu 的电子邮件经过验证
Zachary HorvitzColumbia University在 columbia.edu 的电子邮件经过验证
Shane ParrBrown University在 brown.edu 的电子邮件经过验证
Eric RosenBoston Dynamics AI Institute在 brown.edu 的电子邮件经过验证

Neev Parikh

Brown University, Stripe

在 alumni.brown.edu 的电子邮件经过验证 - 首页


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
Learning Markov state abstractions for deep reinforcement learning C Allen, N Parikh, O Gottesman, G Konidaris Advances in Neural Information Processing Systems 34, 8229-8241, 2021	39	2021
Deep radial-basis value functions for continuous control K Asadi, N Parikh, RE Parr, GD Konidaris, ML Littman Proceedings of the AAAI Conference on Artificial Intelligence, 2021	26*	2021
Automated data extraction from historical city directories: The rise and fall of mid-century gas stations in Providence, RI S Bell, T Marlow, K Wombacher, A Hitt, N Parikh, A Zsom, S Frickel PloS one 15 (8), e0220219, 2020	14	2020
Locally Observable Markov Decision Processes M Merlin, N Parikh, E Rosen, G Konidaris the ICRA 2020 Workshop on Perception, Action, Learning: From Metric-Semantic …, 2020	7	2020
Robot Task Planning Under Local Observability M Merlin, S Parr, N Parikh, S Orozco, V Gupta, E Rosen, G Konidaris Proceedings of the 2024 IEEE Conference on Robotics and Automation, 2024		2024
Graph Embedding Priors for Multi-task Deep Reinforcement Learning N Parikh, Z Horvitz, N Srinivasan, A Shah, G Konidaris The 4th Knowledge Representation and Reasoning Meets Machine Learning …, 2020		2020

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