Bounding and Counting Linear Regions of Deep Neural Networks

6 November 2017

Papers citing "Bounding and Counting Linear Regions of Deep Neural Networks"

8 / 8 papers shown

Title
Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time Duc Anh Nguyen Ernesto Araya Adalbert Fono Gitta Kutyniok 110 0 0 23 May 2025
NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance Raphael T. Husistein Markus Reiher Marco Eckhoff 196 1 0 20 Feb 2025
A Relative Homology Theory of Representation in Neural Networks Kosio Beshkov 145 0 0 17 Feb 2025
On Space Folds of ReLU Neural Networks Michal Lewandowski Hamid Eghbalzadeh Bernhard Heinzl Raphael Pisoni Bernhard A.Moser MLT 120 1 0 17 Feb 2025
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 125 36 0 29 Apr 2023
Maximum Resilience of Artificial Neural Networks Chih-Hong Cheng Georg Nührenberg Harald Ruess AAML 85 281 0 28 Apr 2017
The Power of Depth for Feedforward Neural Networks Ronen Eldan Ohad Shamir 174 731 0 12 Dec 2015
On the number of response regions of deep feed forward networks with piece-wise linear activations Razvan Pascanu Guido Montúfar Yoshua Bengio FAtt 104 257 0 20 Dec 2013