Neural tangent kernel: Convergence and generalization in neural networks A Jacot, F Gabriel, C Hongler
Advances in neural information processing systems 31, 2018
3014 2018 Scaling description of generalization with number of parameters in deep learning M Geiger, A Jacot, S Spigler, F Gabriel, L Sagun, S d’Ascoli, G Biroli, ...
Journal of Statistical Mechanics: Theory and Experiment 2020 (2), 023401, 2020
206 2020 Convergence of Ising interfaces to Schrammʼs SLE curves D Chelkak, H Duminil-Copin, C Hongler, A Kemppainen, S Smirnov
Comptes Rendus. Mathématique 352 (2), 157-161, 2014
194 2014 Conformal invariance of spin correlations in the planar Ising model D Chelkak, C Hongler, K Izyurov
Annals of Mathematics, Pages 1087-1138 from Volume 181, Issue 3, 2015
175 2015 Connection probabilities and RSW‐type bounds for the two‐dimensional FK Ising model H Duminil‐Copin, C Hongler, P Nolin
Communications on pure and applied mathematics 64 (9), 1165-1198, 2011
121 * 2011 The energy density in the planar Ising model C Hongler, S Smirnov
Acta Mathematica, Issue 2, pp 191–225, 2013
115 * 2013 Implicit regularization of random feature models A Jacot, B Simsek, F Spadaro, C Hongler, F Gabriel
International Conference on Machine Learning, 4631-4640, 2020
87 2020 The scaling limit of critical Ising interfaces is S Benoist, C Hongler
73 2019 Crossing probabilities in topological rectangles for the critical planar FK-Ising model D Chelkak, H Duminil-Copin, C Hongler
71 2016 Geometry of the loss landscape in overparameterized neural networks: Symmetries and invariances B Simsek, F Ged, A Jacot, F Spadaro, C Hongler, W Gerstner, J Brea
International Conference on Machine Learning, 9722-9732, 2021
70 2021 Conformal invariance of Ising model correlations C Hongler
XVIIth International Congress on Mathematical Physics, 326-335, 2013
67 2013 Ising interfaces and free boundary conditions C Hongler, K Kytölä
Journal of the American Mathematical Society 26 (4), 1107-1189, 2013
67 * 2013 Kernel alignment risk estimator: Risk prediction from training data A Jacot, B Simsek, F Spadaro, C Hongler, F Gabriel
Advances in neural information processing systems 33, 15568-15578, 2020
54 2020 Saddle-to-saddle dynamics in deep linear networks: Small initialization training, symmetry, and sparsity A Jacot, F Ged, B Şimşek, C Hongler, F Gabriel
arXiv preprint arXiv:2106.15933, 2021
32 2021 The asymptotic spectrum of the hessian of dnn throughout training A Jacot, F Gabriel, C Hongler
arXiv preprint arXiv:1910.02875, 2019
29 2019 Conformal invariance of crossing probabilities for the Ising model with free boundary conditions S Benoist, H Duminil-Copin, C Hongler
22 2016 Ising Model: Local Spin Correlations and Conformal Invariance R Gheissari, C Hongler, S Park
arXiv preprint arXiv:1312.4446, 2016
21 2016 Critical percolation: the expected number of clusters in a rectangle C Hongler, S Smirnov
Probability theory and related fields 151, 735-756, 2011
20 2011 Correlations of primary fields in the critical Ising model D Chelkak, C Hongler, K Izyurov
arXiv preprint arXiv:2103.10263, 2021
19 2021 Freeze and chaos for dnns: an ntk view of batch normalization, checkerboard and boundary effects A Jacot, F Gabriel, C Hongler
arXiv preprint arXiv:1907.05715 6, 2019
18 2019 
Dmitry ChelkakUniversity of MichiganAdresse e-mail validée de umich.edu
