Bobak T. Kiani

Quantum, 2024

Hardness of Learning Neural Networks under the Manifold Hypothesis.

[BibT_eX]

[DOI]

Jason Wang

Melanie Weber

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Unitary Convolutions for Learning on Graphs and Groups.

[BibT_eX]

[DOI]

Lukas Fesser

Melanie Weber

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

On the hardness of learning under symmetries.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Efficient classical algorithms for simulating symmetric quantum systems.

[BibT_eX]

[DOI]

Quantum, November, 2023

Horizons of Artificial Intelligence in Quantum Computation

[BibT_eX]

[DOI]

PhD thesis, 2023

Neural Networks for Programming Quantum Annealers.

[BibT_eX]

[DOI]

CoRR, 2023

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Equivariant Polynomials for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

The SSL Interplay: Augmentations, Inductive Bias, and Generalization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Block-encoding dense and full-rank kernels using hierarchical matrices: applications in quantum numerical linear algebra.

[BibT_eX]

[DOI]

Quynh T. Nguyen

Quantum, September, 2022

Joint Embedding Self-Supervised Learning in the Kernel Regime.

[BibT_eX]

[DOI]

CoRR, 2022

Quantum algorithm for dense kernel matrices using hierarchical splitting.

[BibT_eX]

[DOI]

Quynh The Nguyen

CoRR, 2022

projUNN: efficient method for training deep networks with unitary matrices.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Implicit Bias of Linear Equivariant Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Quantum algorithms for group convolution, cross-correlation, and equivariant transformations.

[BibT_eX]

[DOI]

CoRR, 2021

Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data.

[BibT_eX]

[DOI]

CoRR, 2021

Adversarial Robustness Guarantees for Random Deep Neural Networks.

[BibT_eX]

[DOI]

Giacomo De Palma

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Quantum advantage for differential equation analysis.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Unitaries by Gradient Descent.

[BibT_eX]

[DOI]

Reevu Maity

CoRR, 2020

2019

Random deep neural networks are biased towards simple functions.

[BibT_eX]

[DOI]

Giacomo De Palma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Deep neural networks are biased towards simple functions.

[BibT_eX]

[DOI]

Giacomo De Palma