Jingtong Su

202120222023202413 24 42 23

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Julia KempeCDS and Courant Institute, NYUVerified email at nyu.edu
Nikolaos TsilivisNew York UniversityVerified email at nyu.edu
Ruiqi GaoPhD Student, Princeton UniversityVerified email at princeton.edu
Tianle CaiPhD Student, Princeton UniversityVerified email at princeton.edu
Liwei WangProfessor, Peking UniversityVerified email at cis.pku.edu.cn
Yihang ChenEPFLVerified email at epfl.ch
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerified email at princeton.edu
Miles CranmerUniversity of CambridgeVerified email at cam.ac.uk
Drummond FieldingFlatiron Research Fellow, Flatiron Institute, Center for Computational AstrophysicsVerified email at flatironinstitute.org
Shirley HoFlatiron Institute, Center for Computational AstrophysicsVerified email at flatironinstitute.org
Yifei WangMITVerified email at mit.edu
Yisen WangAssistant Professor, Peking UniversityVerified email at pku.edu.cn
Ya Shi ZhangStudent, University of CambridgeVerified email at cam.ac.uk

Jingtong Su

Verified email at nyu.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot J Su, Y Chen, T Cai, T Wu, R Gao, L Wang, JD Lee NeurIPS 2020; arXiv preprint arXiv:2009.11094, 2020	77	2020
Can we achieve robustness from data alone? N Tsilivis, J Su, J Kempe ICML Workshop on New Frontiers in Adversarial Machine Learning, 2022, 2022	17	2022
Adversarial Noise Injection for Learned Turbulence Simulations J Su, J Kempe, D Fielding, N Tsilivis, M Cranmer, S Ho NeurIPS Workshop on Machine Learning and the Physical Sciences, 2022, 2022	5	2022
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization S Xin, Y Wang, J Su, Y Wang AAAI 2023, 2022	2	2022
Domain-wise Adversarial Training for Out-of-Distribution Generalization S Xin, Y Wang, J Su, Y Wang	1	2022
Wavelets Beat Monkeys at Adversarial Robustness J Su, J Kempe NeurIPS Workshop on Machine Learning and the Physical Sciences, 2022, 2022	1	2022
On the Robustness of Neural Collapse and the Neural Collapse of Robustness J Su, YS Zhang, N Tsilivis, J Kempe Transactions on Machine Learning Research, 0	1*
Mission Impossible: A Statistical Perspective on Jailbreaking LLMs J Su, J Kempe, K Ullrich ICML 2024 Workshop on Theoretical Foundations of Foundation Models, 0

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