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
Wieland BrendelFellow at ELLIS Institut Tübingen, Group Leader, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Huan ZhangAssistant Professor at University of Illinois Urbana-ChampaignVerified email at illinois.edu
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 DeepMind, UC BerkeleyVerified email at google.com
Yilun DuHarvard University / Google DeepmindVerified email at seas.harvard.edu
Ferenc HuszárUniversity of CambridgeVerified email at cam.ac.uk
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
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	2311	2017
Generating natural language adversarial examples M Alzantot, Y Sharma, A Elgohary, BJ Ho, M Srivastava, KW Chang EMNLP 2018, 2018	1139	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	1026*	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	724	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	364*	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	333	2021
Genattack: Practical black-box attacks with gradient-free optimization M Alzantot, Y Sharma, S Chakraborty, M Srivastava GECCO 2019, 2018	312	2018
Contrastive Learning Inverts the Data Generating Process RS Zimmermann, Y Sharma, S Schneider*, M Bethge, W Brendel ICML 2021, 2021	256	2021
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	153*	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	152	2020
Attacking the Madry Defense Model with -based Adversarial Examples Y Sharma, PY Chen ICLR 2018 Workshops, 2017	131*	2017
On the Effectiveness of Low Frequency Perturbations Y Sharma, GW Ding, M Brubaker IJCAI 2019, 2019	130	2019
Are Generative Classifiers More Robust to Adversarial Attacks? Y Li, J Bradshaw, Y Sharma ICML 2019, 2018	110	2018
Unsupervised Learning of Compositional Energy Concepts Y Du, S Li, Y Sharma, JB Tenenbaum, I Mordatch NeurIPS 2021, 2021	87	2021
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	45	2024
Bypassing feature squeezing by increasing adversary strength Y Sharma, PY Chen arXiv preprint arXiv:1803.09868, 2018	42	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	40*	2020
Provably Learning Object-Centric Representations J Brady, RS Zimmermann, Y Sharma, B Schölkopf, J von Kügelgen, ... ICML 2023, 2023	38	2023
Jacobian-based Causal Discovery with Nonlinear ICA P Reizinger, Y Sharma, M Bethge, B Schölkopf, F Huszár, W Brendel TMLR 2023, 2023	21	2023
Spatially structured recurrent modules N Rahaman, A Goyal, MW Gondal, M Wuthrich, S Bauer, Y Sharma, ... ICLR 2021, 2020	19*	2020

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