The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization

7 June 2021

Papers citing "The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization"

10 / 10 papers shown

Title
On the Neural Tangent Kernel of Equilibrium Models Zhili Feng J. Zico Kolter 20 6 0 21 Oct 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 40 14 0 23 May 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks Blake Bordelon Cengiz Pehlevan MLT 40 29 0 06 Apr 2023
Width and Depth Limits Commute in Residual Networks Soufiane Hayou Greg Yang 47 14 0 01 Feb 2023
Meta-Principled Family of Hyperparameter Scaling Strategies Sho Yaida 58 16 0 10 Oct 2022
Dynamical Isometry for Residual Networks Advait Gadhikar R. Burkholz ODL AI4CE 40 2 0 05 Oct 2022
Precise characterization of the prior predictive distribution of deep ReLU networks Lorenzo Noci Gregor Bachmann Kevin Roth Sebastian Nowozin Thomas Hofmann BDL UQCV 29 32 0 11 Jun 2021
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 46 51 0 24 Oct 2020
Deep Networks and the Multiple Manifold Problem Sam Buchanan D. Gilboa John N. Wright 166 39 0 25 Aug 2020
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach Grant M. Rotskoff Eric Vanden-Eijnden 68 118 0 02 May 2018