Sharma, Yash

20 publications

CoRL 2024 MOSAIC: Modular Foundation Models for Assistive and Interactive Cooking Huaxiaoyue Wang, Kushal Kedia, Juntao Ren, Rahma Abdullah, Atiksh Bhardwaj, Angela Chao, Kelly Y Chen, Nathaniel Chin, Prithwish Dan, Xinyi Fan, Gonzalo Gonzalez-Pumariega, Aditya Kompella, Maximus Adrian Pace, Yash Sharma, Xiangwan Sun, Neha Sunkara, Sanjiban Choudhury

NeurIPS 2024 No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance Vishaal Udandarao, Ameya Prabhu, Adhiraj Ghosh, Yash Sharma, Philip H.S. Torr, Adel Bibi, Samuel Albanie, Matthias Bethge

NeurIPSW 2024 Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu, Matthias Bethge, Wieland Brendel

NeurIPS 2023 Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought Yuki Wang, Gonzalo Gonzalez-Pumariega, Yash Sharma, Sanjiban Choudhury

TMLR 2023 Jacobian-Based Causal Discovery with Nonlinear ICA Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel

NeurIPS 2023 On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks Laura F. Nern, Harsh Raj, Maurice André Georgi, Yash Sharma

ICML 2023 Provably Learning Object-Centric Representations Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius Von Kügelgen, Wieland Brendel

CLeaR 2022 Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sebastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien

ICMLW 2022 Pixel-Level Correspondence for Self-Supervised Learning from Video Yash Sharma, Yi Zhu, Chris Russell, Thomas Brox

MLHC 2022 Weakly Supervised Deep Instance Nuclei Detection Using Points Annotation in 3D Cardiovascular Immunofluorescent Images Nazanin Moradinasab, Yash Sharma, Laura S. Shankman, Gary K. Owens, Donald E. Brown

JMLR 2021 Benchmarking Unsupervised Object Representations for Video Sequences Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker

ICML 2021 Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel

NeurIPS 2021 Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello

ICLR 2021 Spatially Structured Recurrent Modules Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf

ICLR 2021 Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan Paiton

NeurIPS 2021 Unsupervised Learning of Compositional Energy Concepts Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch

ICLR 2020 MMA Training: Direct Input Space Margin Maximization Through Adversarial Training Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui, Ruitong Huang

ICML 2019 Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li, John Bradshaw, Yash Sharma

IJCAI 2019 On the Effectiveness of Low Frequency Perturbations Yash Sharma, Gavin Weiguang Ding, Marcus A. Brubaker

AAAI 2018 EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh