Nikita Dhawan

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Sergey LevineUC Berkeley, Physical IntelligenceVerified email at eecs.berkeley.edu
Marvin ZhangUC BerkeleyVerified email at eecs.berkeley.edu
Chelsea FinnStanford University, GoogleVerified email at cs.stanford.edu
Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
Laura SmithUC BerkeleyVerified email at berkeley.edu
Abhishek GuptaUniversity of WashingtonVerified email at cs.washington.edu
Adam DziedzicSrpintML group at CISPA, Vector Institute & University of TorontoVerified email at cispa.de
Muhammad Ahmad KaleemUniversity of TorontoVerified email at mail.utoronto.ca
Nicolas PapernotUniversity of Toronto and Vector InstituteVerified email at utoronto.ca
Haonan DuanUniversity of TorontoVerified email at cs.toronto.edu
Franziska BoenischAssistant Professor, CISPA Helmholtz Center for Information SecurityVerified email at cispa.de
Roger GrosseAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Juhan BaeGraduate Student, University of TorontoVerified email at cs.toronto.edu
Sicong(Sheldon) HuangUniversity of TorontoVerified email at cs.toronto.edu

Nikita Dhawan

Verified email at cs.toronto.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Adaptive risk minimization: Learning to adapt to domain shift M Zhang, H Marklund, N Dhawan, A Gupta, S Levine, C Finn Advances in Neural Information Processing Systems 34, 23664-23678, 2021	254*	2021
Avid: Learning multi-stage tasks via pixel-level translation of human videos L Smith, N Dhawan, M Zhang, P Abbeel, S Levine arXiv preprint arXiv:1912.04443, 2019	125	2019
On the difficulty of defending self-supervised learning against model extraction A Dziedzic, N Dhawan, MA Kaleem, J Guan, N Papernot International Conference on Machine Learning, 5757-5776, 2022	18	2022
Dataset inference for self-supervised models A Dziedzic, H Duan, MA Kaleem, N Dhawan, J Guan, Y Cattan, ... Advances in Neural Information Processing Systems 35, 12058-12070, 2022	13	2022
Efficient Parametric Approximations of Neural Network Function Space Distance N Dhawan, S Huang, J Bae, RB Grosse International Conference on Machine Learning, 7795-7812, 2023	3	2023
Leveraging Function Space Aggregation for Federated Learning at Scale N Dhawan, N Mitchell, Z Charles, Z Garrett, GK Dziugaite arXiv preprint arXiv:2311.10291, 2023		2023

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