ML Anthology

Kiani, Bobak

9 publications

ICLR 2024 On the Hardness of Learning Under Symmetries Bobak Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
ICML 2023 Equivariant Polynomials for Graph Neural Networks Omri Puny, Derek Lim, Bobak Kiani, Haggai Maron, Yaron Lipman
NeurIPS 2023 Self-Supervised Learning with Lie Symmetries for Partial Differential Equations Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani
ICLRW 2023 Self-Supervised Learning with Lie Symmetries for Partial Differential Equations Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani
ICML 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann Lecun, Alberto Bietti
ICLRW 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
NeurIPS 2022 projUNN: Efficient Method for Training Deep Networks with Unitary Matrices Bobak Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
ICML 2021 Adversarial Robustness Guarantees for Random Deep Neural Networks Giacomo De Palma, Bobak Kiani, Seth Lloyd
NeurIPS 2019 Random Deep Neural Networks Are Biased Towards Simple Functions Giacomo De Palma, Bobak Kiani, Seth Lloyd