On the Expected Complexity of Maxout Networks

1 July 2021

Papers citing "On the Expected Complexity of Maxout Networks"

7 / 7 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 99 33 0 29 Apr 2023
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions Junyang Cai Khai-Nguyen Nguyen Nishant Shrestha Aidan Good Ruisen Tu Xin Yu Shandian Zhe Thiago Serra MLT 40 7 0 19 Jan 2023
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization Hanna Tseran Guido Montúfar ODL 35 0 0 17 Jan 2023
On the Number of Regions of Piecewise Linear Neural Networks Alexis Goujon Arian Etemadi M. Unser 54 14 0 17 Jun 2022
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks Hao Chen Yu Wang Huan Xiong GNN 24 6 0 01 Jun 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu Thiago Serra Srikumar Ramalingam Shandian Zhe 46 48 0 09 Mar 2022
Benefits of depth in neural networks Matus Telgarsky 179 604 0 14 Feb 2016