Arthur Jacot

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 31

Top Topics

Attraction Repulsion

Nonlinear Functions

Top Venues

Publications

Yuxiao Wen, Arthur Jacot
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning. CoRR (2024)
Arthur Jacot, Seok Hoan Choi, Yuxiao Wen
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning. CoRR (2024)
Arthur Jacot, Alexandre Kaiser
Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets. CoRR (2024)
Zihan Wang, Arthur Jacot
Implicit bias of SGD in L2-regularized linear DNNs: One-way jumps from high to low rank. ICLR (2024)
Zhenfeng Tu, Santiago Aranguri, Arthur Jacot
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes. CoRR (2024)
Arthur Jacot
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff. CoRR (2023)
Arthur Jacot
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions. ICLR (2023)
Zihan Wang, Arthur Jacot
-regularized linear DNNs: One-way jumps from high to low rank. CoRR (2023)
Arthur Jacot
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff. NeurIPS (2023)
Arthur Jacot, Eugene Golikov, Clément Hongler, Franck Gabriel
-regularized DNNs: Attraction/Repulsion and Sparsity. CoRR (2022)
Arthur Jacot
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions. CoRR (2022)
Arthur Jacot, Eugene Golikov, Clément Hongler, Franck Gabriel
Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity. NeurIPS (2022)
Arthur Jacot, Franck Gabriel, François Ged, Clément Hongler
Freeze and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts. MSML (2022)
Benjamin Dupuis, Arthur Jacot
DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. NeurIPS (2021)
Arthur Jacot, François Ged, Franck Gabriel, Berfin Simsek, Clément Hongler
Deep Linear Networks Dynamics: Low-Rank Biases Induced by Initialization Scale and L2 Regularization. CoRR (2021)
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. CoRR (2021)
Arthur Jacot, Franck Gabriel, Clément Hongler
Neural tangent kernel: convergence and generalization in neural networks (invited paper). STOC (2021)
Benjamin Dupuis, Arthur Jacot
DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. CoRR (2021)
Yatin Dandi, Arthur Jacot
Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis. CoRR (2021)
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. ICML (2021)
Arthur Jacot, Franck Gabriel, Clément Hongler
The asymptotic spectrum of the Hessian of DNN throughout training. ICLR (2020)
Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
Implicit Regularization of Random Feature Models. CoRR (2020)
Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
Implicit Regularization of Random Feature Models. ICML (2020)
Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
Kernel Alignment Risk Estimator: Risk Prediction from Training Data. CoRR (2020)
Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
Kernel Alignment Risk Estimator: Risk Prediction from Training Data. NeurIPS (2020)
Mario Geiger, Arthur Jacot, Stefano Spigler, Franck Gabriel, Levent Sagun, Stéphane d'Ascoli, Giulio Biroli, Clément Hongler, Matthieu Wyart
Scaling description of generalization with number of parameters in deep learning. CoRR (2019)
Arthur Jacot, Franck Gabriel, Clément Hongler
The asymptotic spectrum of the Hessian of DNN throughout training. CoRR (2019)
Mario Geiger, Stefano Spigler, Arthur Jacot, Matthieu Wyart
Disentangling feature and lazy learning in deep neural networks: an empirical study. CoRR (2019)
Arthur Jacot, Franck Gabriel, Clément Hongler
Freeze and Chaos for DNNs: an NTK view of Batch Normalization, Checkerboard and Boundary Effects. CoRR (2019)
Arthur Jacot, Franck Gabriel, Clément Hongler
Neural Tangent Kernel: Convergence and Generalization in Neural Networks. CoRR (2018)
Arthur Jacot, Clément Hongler, Franck Gabriel
Neural Tangent Kernel: Convergence and Generalization in Neural Networks. NeurIPS (2018)