Yash Sharma

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Pin-Yu ChenPrincipal Research Scientist, IBM Research AI; MIT-IBM Watson AI Lab; RPI-IBM AIRCVerified email at ibm.com
Huan ZhangAssistant Professor at University of Illinois Urbana-ChampaignVerified email at illinois.edu
Wieland BrendelFellow at ELLIS Institut Tübingen, Group Leader, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Matthias BethgeTübingen University & Maddox Co-FounderVerified email at bethgelab.org
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Ian GoodfellowDeepMindVerified email at deepmind.com
Kai-Wei ChangAssociate Professor, UCLAVerified email at kwchang.net
Nicolas PapernotUniversity of Toronto and Vector InstituteVerified email at utoronto.ca
Julius von KügelgenETH ZürichVerified email at stat.math.ethz.ch
Marcus A BrubakerResearch Scientist, Google DeepMind; Associate Prof, York University; Affiliate, Vector InstituteVerified email at yorku.ca
Andreas GeigerProfessor of Computer Science, University of Tübingen and Tübingen AI CenterVerified email at uni-tuebingen.de
Alexander S. EckerUniversity of Göttingen, GermanyVerified email at cs.uni-goettingen.de
Joshua B. TenenbaumMITVerified email at mit.edu
Igor MordatchGoogle DeepMindVerified email at google.com
Yilun DuHarvard University / Google DeepmindVerified email at seas.harvard.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Ferenc HuszárUniversity of CambridgeVerified email at cam.ac.uk
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
Thomas BroxUniversity of FreiburgVerified email at cs.uni-freiburg.de
Nicholas CarliniGoogle DeepMindVerified email at google.com

Yash Sharma

University of Tübingen, Max Planck Institute for Intelligent Systems

Verified email at bethgelab.org - Homepage

Artificial Intelligence Machine Learning


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Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models PY Chen, H Zhang, Y Sharma, J Yi, CJ Hsieh Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017	2192	2017
Generating natural language adversarial examples M Alzantot, Y Sharma, A Elgohary, BJ Ho, M Srivastava, KW Chang EMNLP 2018, 2018	1091	2018
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library N Papernot, F Faghri, N Carlini, I Goodfellow, R Feinman, A Kurakin, ... arXiv preprint arXiv:1610.00768, 2018	998*	2018
EAD: elastic-net attacks to deep neural networks via adversarial examples PY Chen, Y Sharma, H Zhang, J Yi, CJ Hsieh AAAI 2018, 2017	708	2017
Max-Margin Adversarial (MMA) Training: Direct Input Space Margin Maximization through Adversarial Training GW Ding, Y Sharma, KYC Lui, R Huang ICLR 2020, 2018	348*	2018
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style J von Kügelgen, Y Sharma, L Gresele*, W Brendel, B Schölkopf, ... NeurIPS 2021, 2021	306	2021
Genattack: Practical black-box attacks with gradient-free optimization M Alzantot, Y Sharma, S Chakraborty, M Srivastava GECCO 2019, 2018	301	2018
Contrastive Learning Inverts the Data Generating Process RS Zimmermann, Y Sharma, S Schneider*, M Bethge, W Brendel ICML 2021, 2021	228	2021
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding D Klindt, L Schott, Y Sharma*, I Ustyuzhaninov, W Brendel, M Bethge, ... ICLR 2021, 2020	142	2020
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA S Lachapelle, PR López, Y Sharma, K Everett, RL Priol, A Lacoste, ... CLeaR 2022, 2021	139	2021
Attacking the Madry Defense Model with -based Adversarial Examples Y Sharma, PY Chen ICLR 2018 Workshops, 2017	130*	2017
On the Effectiveness of Low Frequency Perturbations Y Sharma, GW Ding, M Brubaker IJCAI 2019, 2019	126	2019
Are Generative Classifiers More Robust to Adversarial Attacks? Y Li, J Bradshaw, Y Sharma ICML 2019, 2018	108	2018
Unsupervised Learning of Compositional Energy Concepts Y Du, S Li, Y Sharma, JB Tenenbaum, I Mordatch NeurIPS 2021, 2021	79	2021
Bypassing feature squeezing by increasing adversary strength Y Sharma, PY Chen arXiv preprint arXiv:1803.09868, 2018	41	2018
Benchmarking Unsupervised Object Representations for Video Sequences MA Weis, K Chitta, Y Sharma, W Brendel, M Bethge, A Geiger, AS Ecker JMLR 2021, 2020	39*	2020
No" Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance V Udandarao, A Prabhu, A Ghosh, Y Sharma, PHS Torr, A Bibi, S Albanie, ... NeurIPS 2024, 2024	32	2024
Provably Learning Object-Centric Representations J Brady, RS Zimmermann, Y Sharma, B Schölkopf, J von Kügelgen, ... ICML 2023, 2023	29	2023
Spatially structured recurrent modules N Rahaman, A Goyal, MW Gondal, M Wuthrich, S Bauer, Y Sharma, ... ICLR 2021, 2020	19*	2020
Jacobian-based Causal Discovery with Nonlinear ICA P Reizinger, Y Sharma, M Bethge, B Schölkopf, F Huszár, W Brendel TMLR 2023, 2023	18	2023

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