← Authors

Arthur Jacot

15 papers · 2018–2025 · 3 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (3) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (4) πŸ—ΊοΈ Taxonomy Completionist (13) πŸŒ‰ Interdisciplinary Bridge πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (15) ❓ The Questioner

Conferences

ICLR (6) NIPS (6) ICML (3)

Top co-authors

Clement Hongler (6) Franck Gabriel (5) Berfin Simsek (3) Francesco Spadaro (3) Yuxiao Wen (2) Zihan Wang (2) Santiago Aranguri (1) Nicholas Matthew Boffi (1) Ingvar Ziemann (1) Seok Hoan Choi (1)

Keywords

kernel ridge regression (2) feature learning (2) deep neural network (2) learning theory (2) kernel methods (2) gaussian process (1) generalization error (1) l2 regularization (1) random matrix theory (1) implicit regularization (1) linear network (1) training dynamics (1) hidden representation (1) lazy regime (1) affine subspace (1) random feature model (1) critical point (1) overparameterized neural network (1) risk prediction (1) kernel alignment (1)

Papers

Shallow diffusion networks provably learn hidden low-dimensional structure ICLR 2025
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning ICLR 2025
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse ICLR 2025
Implicit bias of SGD in $L_2$-regularized linear DNNs: One-way jumps from high to low rank ICLR 2024
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning ICML 2024
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes NIPS 2024
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions ICLR 2023
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff NIPS 2023
Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity NIPS 2022
DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel NIPS 2021
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances ICML 2021
Implicit Regularization of Random Feature Models ICML 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
The asymptotic spectrum of the Hessian of DNN throughout training ICLR 2020
Neural Tangent Kernel: Convergence and Generalization in Neural Networks NIPS 2018