Franck Gabriel

J. Econ. Theory, 2022

Feature Learning in L<sub>2</sub>-regularized DNNs: Attraction/Repulsion and Sparsity.

[BibT_eX]

[DOI]

CoRR, 2022

Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity.

[BibT_eX]

[DOI]

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

Freeze and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts.

[BibT_eX]

[DOI]

Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021

Deep Linear Networks Dynamics: Low-Rank Biases Induced by Initialization Scale and L2 Regularization.

[BibT_eX]

[DOI]

CoRR, 2021

Smart Proofs via Smart Contracts: Succinct and Informative Mathematical Derivations via Decentralized Markets.

[BibT_eX]

[DOI]

CoRR, 2021

Neural tangent kernel: convergence and generalization in neural networks (invited paper).

[BibT_eX]

[DOI]

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

2020

Kernel Alignment Risk Estimator: Risk Prediction from Training Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Implicit Regularization of Random Feature Models.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

The asymptotic spectrum of the Hessian of DNN throughout training.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Freeze and Chaos for DNNs: an NTK view of Batch Normalization, Checkerboard and Boundary Effects.

[BibT_eX]

[DOI]

CoRR, 2019

Scaling description of generalization with number of parameters in deep learning.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Neural Tangent Kernel: Convergence and Generalization in Neural Networks.

[BibT_eX]

[DOI]