Arthur Jacot - RankMe

42 papers A* 16Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Polynomial Speedup in Diffusion Models with the Multilevel Euler-Maruyama Method. CoRR Arthur Jacot
2025	J	`jnl`	Deep Learning as a Convex Paradigm of Computation: Minimizing Circuit Size with ResNets. CoRR Arthur Jacot
2025	—	`conf`	Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets. CPAL Arthur Jacot, Alexandre Kaiser
2025	A*	`conf`	How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning. ICLR Arthur Jacot, Seok Hoan Choi, Yuxiao Wen
2025	J	`jnl`	Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape. CoRR Ioannis Bantzis, James B. Simon, Arthur Jacot
2025	A*	`conf`	Shallow diffusion networks provably learn hidden low-dimensional structure. ICLR Nicholas Matthew Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann
2025	A*	`conf`	Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse. ICLR Arthur Jacot, Peter Súkeník, Zihan Wang, Marco Mondelli
2024	J	`jnl`	Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets. CoRR Arthur Jacot, Alexandre Kaiser
2024	J	`jnl`	How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning. CoRR Arthur Jacot, Seok Hoan Choi, Yuxiao Wen
2024	A*	`conf`	Implicit bias of SGD in L2-regularized linear DNNs: One-way jumps from high to low rank. ICLR Zihan Wang, Arthur Jacot
2024	A*	`conf`	Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes. NeurIPS Zhenfeng Tu, Santiago Aranguri, Arthur Jacot
2024	J	`jnl`	Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes. CoRR Zhenfeng Tu, Santiago Aranguri, Arthur Jacot
2024	J	`jnl`	Shallow diffusion networks provably learn hidden low-dimensional structure. CoRR Nicholas M. Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann
2024	A*	`conf`	Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning. ICML Yuxiao Wen, Arthur Jacot
2024	J	`jnl`	Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning. CoRR Yuxiao Wen, Arthur Jacot
2024	J	`jnl`	Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse. CoRR Arthur Jacot, Peter Súkeník, Zihan Wang, Marco Mondelli
2023	A*	`conf`	Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff. NeurIPS Arthur Jacot
2023	J	`jnl`	Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff. CoRR Arthur Jacot
2023	A*	`conf`	Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions. ICLR Arthur Jacot
2023	J	`jnl`	Implicit bias of SGD in L CoRR Zihan Wang, Arthur Jacot
2022	A*	`conf`	Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity. NeurIPS Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel
2022	J	`jnl`	Feature Learning in L CoRR Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel
2022	—	`conf`	Freeze and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts. MSML Arthur Jacot, Franck Gabriel, François Ged, Clément Hongler
2022	J	`jnl`	Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions. CoRR Arthur Jacot
2021	J	`jnl`	DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. CoRR Benjamin Dupuis, Arthur Jacot
2021	A*	`conf`	DNN-based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel. NeurIPS Benjamin Dupuis, Arthur Jacot
2021	J	`jnl`	Deep Linear Networks Dynamics: Low-Rank Biases Induced by Initialization Scale and L2 Regularization. CoRR Arthur Jacot, François Ged, Franck Gabriel, Berfin Simsek, Clément Hongler
2021	A*	`conf`	Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. ICML Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea
2021	J	`jnl`	Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances. CoRR Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea
2021	A*	`conf`	Neural tangent kernel: convergence and generalization in neural networks (invited paper). STOC Arthur Jacot, Franck Gabriel, Clément Hongler
2021	J	`jnl`	Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis. CoRR Yatin Dandi, Arthur Jacot
2020	A*	`conf`	Implicit Regularization of Random Feature Models. ICML Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
2020	J	`jnl`	Implicit Regularization of Random Feature Models. CoRR Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
2020	A*	`conf`	Kernel Alignment Risk Estimator: Risk Prediction from Training Data. NeurIPS Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
2020	J	`jnl`	Kernel Alignment Risk Estimator: Risk Prediction from Training Data. CoRR Arthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel
2020	A*	`conf`	The asymptotic spectrum of the Hessian of DNN throughout training. ICLR Arthur Jacot, Franck Gabriel, Clément Hongler
2019	J	`jnl`	Disentangling feature and lazy learning in deep neural networks: an empirical study. CoRR Mario Geiger, Stefano Spigler, Arthur Jacot, Matthieu Wyart
2019	J	`jnl`	Freeze and Chaos for DNNs: an NTK view of Batch Normalization, Checkerboard and Boundary Effects. CoRR Arthur Jacot, Franck Gabriel, Clément Hongler
2019	J	`jnl`	Scaling description of generalization with number of parameters in deep learning. CoRR Mario Geiger, Arthur Jacot, Stefano Spigler, Franck Gabriel, Levent Sagun, Stéphane d'Ascoli, Giulio Biroli, Clément Hongler, Matthieu Wyart
2019	J	`jnl`	The asymptotic spectrum of the Hessian of DNN throughout training. CoRR Arthur Jacot, Franck Gabriel, Clément Hongler
2018	A*	`conf`	Neural Tangent Kernel: Convergence and Generalization in Neural Networks. NeurIPS Arthur Jacot, Clément Hongler, Franck Gabriel
2018	J	`jnl`	Neural Tangent Kernel: Convergence and Generalization in Neural Networks. CoRR Arthur Jacot, Franck Gabriel, Clément Hongler