Data Representations' Study of Latent Image Manifolds

31 May 2023

Papers citing "Data Representations' Study of Latent Image Manifolds"

10 / 10 papers shown

Title
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks Tolga Birdal Aaron Lou Leonidas Guibas Umut cSimcsekli 52 61 0 25 Nov 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 226 264 0 18 Apr 2021
Deep Networks and the Multiple Manifold Problem Sam Buchanan D. Gilboa John N. Wright 173 39 0 25 Aug 2020
Hierarchical nucleation in deep neural networks Diego Doimo Aldo Glielmo A. Ansuini Alessandro Laio BDL AI4CE 30 31 0 07 Jul 2020
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 153 769 0 12 Nov 2018
Latent Space Oddity: on the Curvature of Deep Generative Models Georgios Arvanitidis Lars Kai Hansen Søren Hauberg DRL 93 267 0 31 Oct 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 621 3,264 0 24 Nov 2016
Exponential expressivity in deep neural networks through transient chaos Ben Poole Subhaneil Lahiri M. Raghu Jascha Narain Sohl-Dickstein Surya Ganguli 86 587 0 16 Jun 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.3K 39,383 0 01 Sep 2014
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 202 12,384 0 24 Jun 2012