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Bobak T. Kiani
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2020 – today
- 2024
- [c8]Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber:
On the hardness of learning under symmetries. ICLR 2024 - [i17]Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber:
On the hardness of learning under symmetries. CoRR abs/2401.01869 (2024) - [i16]Bobak T. Kiani, Jason Wang, Melanie Weber:
Hardness of Learning Neural Networks under the Manifold Hypothesis. CoRR abs/2406.01461 (2024) - [i15]Bobak T. Kiani, Lukas Fesser, Melanie Weber:
Unitary convolutions for learning on graphs and groups. CoRR abs/2410.05499 (2024) - 2023
- [b1]Bobak T. Kiani:
Horizons of Artificial Intelligence in Quantum Computation. MIT, USA, 2023 - [j2]Eric R. Anschütz, Andreas Bauer, Bobak Toussi Kiani, Seth Lloyd:
Efficient classical algorithms for simulating symmetric quantum systems. Quantum 7: 1189 (2023) - [c7]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML 2023: 3252-3298 - [c6]Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman:
Equivariant Polynomials for Graph Neural Networks. ICML 2023: 28191-28222 - [c5]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS 2023 - [i14]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR abs/2302.02774 (2023) - [i13]Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman:
Equivariant Polynomials for Graph Neural Networks. CoRR abs/2302.11556 (2023) - [i12]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR abs/2307.05432 (2023) - [i11]Samuel Bosch, Bobak Toussi Kiani, Rui Yang, Adrian Lupascu, Seth Lloyd:
Neural Networks for Programming Quantum Annealers. CoRR abs/2308.06807 (2023) - 2022
- [j1]Quynh T. Nguyen, Bobak T. Kiani, Seth Lloyd:
Block-encoding dense and full-rank kernels using hierarchical matrices: applications in quantum numerical linear algebra. Quantum 6: 876 (2022) - [c4]Hannah Lawrence, Bobak Toussi Kiani, Kristian G. Georgiev, Andrew K. Dienes:
Implicit Bias of Linear Equivariant Networks. ICML 2022: 12096-12125 - [c3]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. NeurIPS 2022 - [i10]Quynh The Nguyen, Bobak Toussi Kiani, Seth Lloyd:
Quantum algorithm for dense kernel matrices using hierarchical splitting. CoRR abs/2201.11329 (2022) - [i9]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. CoRR abs/2203.05483 (2022) - [i8]Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun:
Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR abs/2209.14884 (2022) - 2021
- [c2]Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd:
Adversarial Robustness Guarantees for Random Deep Neural Networks. ICML 2021: 2522-2534 - [i7]Bobak Toussi Kiani, Giacomo De Palma, Milad Marvian, Zi-Wen Liu, Seth Lloyd:
Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data. CoRR abs/2101.03037 (2021) - [i6]Grecia Castelazo, Quynh The Nguyen, Giacomo De Palma, Dirk R. Englund, Seth Lloyd, Bobak Toussi Kiani:
Quantum algorithms for group convolution, cross-correlation, and equivariant transformations. CoRR abs/2109.11330 (2021) - [i5]Hannah Lawrence, Kristian Georgiev, Andrew Dienes, Bobak Toussi Kiani:
Implicit Bias of Linear Equivariant Networks. CoRR abs/2110.06084 (2021) - 2020
- [i4]Bobak Toussi Kiani, Seth Lloyd, Reevu Maity:
Learning Unitaries by Gradient Descent. CoRR abs/2001.11897 (2020) - [i3]Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd:
Adversarial robustness guarantees for random deep neural networks. CoRR abs/2004.05923 (2020) - [i2]Bobak Toussi Kiani, Giacomo De Palma, Dirk R. Englund, William M. Kaminsky, Milad Marvian, Seth Lloyd:
Quantum advantage for differential equation analysis. CoRR abs/2010.15776 (2020)
2010 – 2019
- 2019
- [c1]Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd:
Random deep neural networks are biased towards simple functions. NeurIPS 2019: 1962-1974 - 2018
- [i1]Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd:
Deep neural networks are biased towards simple functions. CoRR abs/1812.10156 (2018)
Coauthor Index
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