Bobak Toussi Kiani

21 papers A* 6Journal 15

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Efficient classical algorithms for simulating symmetric quantum systems. Quantum Eric R. Anschuetz, Andreas Bauer, Bobak Toussi Kiani, Seth Lloyd
2023	A*	`conf`	Equivariant Polynomials for Graph Neural Networks. ICML Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023	J	`jnl`	Equivariant Polynomials for Graph Neural Networks. CoRR Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023	J	`jnl`	Neural Networks for Programming Quantum Annealers. CoRR Samuel Bosch, Bobak Toussi Kiani, Rui Yang, Adrian Lupascu, Seth Lloyd
2023	J	`jnl`	Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani
2023	A*	`conf`	The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
2023	J	`jnl`	The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
2022	A*	`conf`	Implicit Bias of Linear Equivariant Networks. ICML Hannah Lawrence, Bobak Toussi Kiani, Kristian G. Georgiev, Andrew K. Dienes
2022	J	`jnl`	Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun
2022	J	`jnl`	Quantum algorithm for dense kernel matrices using hierarchical splitting. CoRR Quynh The Nguyen, Bobak Toussi Kiani, Seth Lloyd
2022	A*	`conf`	projUNN: efficient method for training deep networks with unitary matrices. NeurIPS Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
2022	J	`jnl`	projUNN: efficient method for training deep networks with unitary matrices. CoRR Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
2021	A*	`conf`	Adversarial Robustness Guarantees for Random Deep Neural Networks. ICML Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd
2021	J	`jnl`	Implicit Bias of Linear Equivariant Networks. CoRR Hannah Lawrence, Kristian Georgiev, Andrew Dienes, Bobak Toussi Kiani
2021	J	`jnl`	Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data. CoRR Bobak Toussi Kiani, Giacomo De Palma, Milad Marvian, Zi-Wen Liu, Seth Lloyd
2021	J	`jnl`	Quantum algorithms for group convolution, cross-correlation, and equivariant transformations. CoRR Grecia Castelazo, Quynh The Nguyen, Giacomo De Palma, Dirk R. Englund, Seth Lloyd, Bobak Toussi Kiani
2020	J	`jnl`	Adversarial robustness guarantees for random deep neural networks. CoRR Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd
2020	J	`jnl`	Learning Unitaries by Gradient Descent. CoRR Bobak Toussi Kiani, Seth Lloyd, Reevu Maity
2020	J	`jnl`	Quantum advantage for differential equation analysis. CoRR Bobak Toussi Kiani, Giacomo De Palma, Dirk R. Englund, William M. Kaminsky, Milad Marvian, Seth Lloyd
2019	A*	`conf`	Random deep neural networks are biased towards simple functions. NeurIPS Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd
2018	J	`jnl`	Deep neural networks are biased towards simple functions. CoRR Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd