Arthur Jacot

发表

Disentangling feature and lazy training in deep neural networks

Matthieu Wyart, Mario Geiger, Stefano Spigler, 2019, Journal of Statistical Mechanics: Theory and Experiment.

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

Arthur Jacot, Franck Gabriel, Franccois Ged, 2019 .

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

Levent Sagun, Matthieu Wyart, Giulio Biroli, 2019, Journal of Statistical Mechanics: Theory and Experiment.

Implicit Regularization of Random Feature Models pdf

Arthur Jacot, Franck Gabriel, Clément Hongler, 2020, ICML.

The asymptotic spectrum of the Hessian of DNN throughout training pdf

Arthur Jacot, Franck Gabriel, Cl'ement Hongler, 2020, ICLR.

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

Arthur Jacot, Franck Gabriel, Cl'ement Hongler, 2019, ArXiv.

Kernel Alignment Risk Estimator: Risk Prediction from Training Data pdf

Arthur Jacot, Franck Gabriel, Cl'ement Hongler, 2020, NeurIPS.

Disentangling feature and lazy learning in deep neural networks: an empirical study pdf

Matthieu Wyart, Mario Geiger, Stefano Spigler, 2019, ArXiv.

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

Arthur Jacot, Franck Gabriel, Cl'ement Hongler, 2018, NeurIPS.

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

Arthur Jacot, Franck Gabriel, Franccois Ged, 2021, ArXiv.

DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel pdf

Arthur Jacot, Benjamin Dupuis, Arthur Jacot, 2021, NeurIPS.

Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis pdf

Arthur Jacot, Yatin Dandi, 2021, ArXiv.

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances pdf

Wulfram Gerstner, Johanni Brea, Arthur Jacot, 2021, ICML.