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"

8 / 8 papers shown

Title
On the Neural Tangent Kernel of Equilibrium Models Zhili Feng J. Zico Kolter 16 6 0 21 Oct 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks Blake Bordelon C. Pehlevan MLT 35 29 0 06 Apr 2023
Meta-Principled Family of Hyperparameter Scaling Strategies Sho Yaida 50 16 0 10 Oct 2022
Dynamical Isometry for Residual Networks Advait Gadhikar R. Burkholz ODL AI4CE 32 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 8 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 59 118 0 02 May 2018