Characterizing the Shape of Activation Space in Deep Neural Networks

v1v2 (latest)

Characterizing the Shape of Activation Space in Deep Neural Networks

28 January 2019

ArXiv (abs)PDF HTML

Papers citing "Characterizing the Shape of Activation Space in Deep Neural Networks"

5 / 5 papers shown

Title
Revisiting Point Cloud Completion: Are We Ready For The Real-World? Stuti Pathak Prashant Kumar Nicholus Mboga Gunther Steenackers R. Penne Rudi Penne 521 0 0 26 Nov 2024
GLiDR: Topologically Regularized Graph Generative Network for Sparse LiDAR Point Clouds Prashant Kumar Kshitij Madhav Bhat Vedang Bhupesh Shenvi Nadkarni P. K. Kalra 90 2 0 29 Nov 2023
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 66 2 0 04 Nov 2022
A Fast and Robust Method for Global Topological Functional Optimization Elchanan Solomon Alexander Wagner Paul Bendich 54 22 0 17 Sep 2020
A Topology Layer for Machine Learning Rickard Brüel-Gabrielsson Bradley J. Nelson Anjan Dwaraknath Primoz Skraba Leonidas Guibas Gunnar Carlsson AI4CE 101 134 0 29 May 2019