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
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Wieland BrendelResearch 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; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Kai-Wei ChangAssociate Professor, UCLAVerified email at kwchang.net
Francesco LocatelloTBDVerified email at amazon.com
Marcus A BrubakerAssistant Professor, York University; Faculty 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
Anirudh GoyalDeepMind, Mila, Université de MontréalVerified email at umontreal.ca
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaVerified email at iro.umontreal.ca
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchVerified email at servicenow.com
Joshua B. TenenbaumMITVerified email at mit.edu
Igor MordatchGoogle BrainVerified email at google.com
Ferenc HuszárUniversity of CambridgeVerified email at cam.ac.uk
Thomas BroxUniversity of Freiburg and AmazonVerified email at cs.uni-freiburg.de
Chris RussellAmazonVerified email at amazon.de
Yi ZhuAmazon Web ServicesVerified email at ucmerced.edu

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	1485	2017
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	812*	2018
Generating natural language adversarial examples M Alzantot, Y Sharma, A Elgohary, BJ Ho, M Srivastava, KW Chang EMNLP 2018, 2018	752	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	571	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	225*	2018
Genattack: Practical black-box attacks with gradient-free optimization M Alzantot, Y Sharma, S Chakraborty, M Srivastava GECCO 2019, 2018	208	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	126	2021
Contrastive Learning Inverts the Data Generating Process RS Zimmermann, Y Sharma, S Schneider*, M Bethge, W Brendel ICML 2021, 2021	113	2021
Attacking the Madry Defense Model with -based Adversarial Examples Y Sharma, PY Chen ICLR 2018 Workshops, 2017	109*	2017
Are Generative Classifiers More Robust to Adversarial Attacks? Y Li, J Bradshaw, Y Sharma ICML 2019, 2018	83	2018
On the Effectiveness of Low Frequency Perturbations Y Sharma, GW Ding, M Brubaker IJCAI 2019, 2019	78	2019
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	64	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	35	2021
Bypassing feature squeezing by increasing adversary strength Y Sharma, PY Chen arXiv preprint arXiv:1803.09868, 2018	34	2018
Unsupervised Learning of Compositional Energy Concepts Y Du, S Li, Y Sharma, JB Tenenbaum, I Mordatch NeurIPS 2021, 2021	30	2021
Benchmarking Unsupervised Object Representations for Video Sequences MA Weis, K Chitta, Y Sharma, W Brendel, M Bethge, A Geiger, AS Ecker JMLR 2021, 2020	24*	2020
Spatially structured recurrent modules N Rahaman, A Goyal, MW Gondal, M Wuthrich, S Bauer, Y Sharma, ... ICLR 2021, 2020	19*	2020
CAAD 2018: Generating transferable adversarial examples Y Sharma, TD Le, M Alzantot arXiv preprint arXiv:1810.01268, 2018	11	2018
Gradient-based Adversarial Attacks to Deep Neural Networks in Limited Access Settings Y Sharma Masters thesis, COOPER UNION, 2018	2	2018
How Adversarial Robustness Transfers from Pre-training to Downstream Tasks LF Nern, Y Sharma KDD 2022 Adversarial Workshop, 2022	1	2022

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