On Characterizing the Capacity of Neural Networks using Algebraic Topology

13 February 2018

Papers citing "On Characterizing the Capacity of Neural Networks using Algebraic Topology"

12 / 12 papers shown

Title
A Relative Homology Theory of Representation in Neural Networks Kosio Beshkov 96 0 0 17 Feb 2025
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 24 6 0 06 Jun 2023
Data Topology-Dependent Upper Bounds of Neural Network Widths Sangmin Lee Jong Chul Ye 26 0 0 25 May 2023
Experimental Observations of the Topology of Convolutional Neural Network Activations Emilie Purvine Davis Brown Brett Jefferson C. Joslyn Brenda Praggastis Archit Rathore Madelyn Shapiro Bei Wang Youjia Zhou AI4CE 40 12 0 01 Dec 2022
Zeroth-Order Topological Insights into Iterative Magnitude Pruning Aishwarya H. Balwani J. Krzyston 24 2 0 14 Jun 2022
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks Hao Chen Yu Wang Huan Xiong GNN 14 6 0 01 Jun 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 19 11 0 19 Apr 2022
Activation Landscapes as a Topological Summary of Neural Network Performance Matthew Wheeler Jose J. Bouza Peter Bubenik 28 19 0 19 Oct 2021
Topologically Densified Distributions Christoph Hofer Florian Graf Marc Niethammer Roland Kwitt 24 15 0 12 Feb 2020
Topological Data Analysis of Decision Boundaries with Application to Model Selection K. Ramamurthy Kush R. Varshney Krishnan Mody 9 40 0 25 May 2018
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,326 0 05 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016