On the non-universality of deep learning: quantifying the cost of symmetry

5 August 2022

Papers citing "On the non-universality of deep learning: quantifying the cost of symmetry"

5 / 5 papers shown

Title
Theoretical Analysis of Inductive Biases in Deep Convolutional Networks Zihao Wang Lei Wu 23 19 0 15 May 2023
A Mathematical Model for Curriculum Learning for Parities Elisabetta Cornacchia Elchanan Mossel 34 10 0 31 Jan 2023
On the Power of Differentiable Learning versus PAC and SQ Learning Emmanuel Abbe Pritish Kamath Eran Malach Colin Sandon Nathan Srebro MLT 71 23 0 09 Aug 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,104 0 27 Apr 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 46 89 0 25 Feb 2021