Mad Max: Affine Spline Insights into Deep Learning

Mad Max: Affine Spline Insights into Deep Learning

17 May 2018

Randall Balestriero

Richard Baraniuk

Papers citing "Mad Max: Affine Spline Insights into Deep Learning"

10 / 10 papers shown

Title
On the Geometry of Deep Learning Randall Balestriero Ahmed Imtiaz Humayun Richard G. Baraniuk AI4CE 31 1 0 09 Aug 2024
A max-affine spline approximation of neural networks using the Legendre transform of a convex-concave representation Adam Perrett Danny Wood Gavin Brown 9 0 0 16 Jul 2023
SpecXAI -- Spectral interpretability of Deep Learning Models Stefan Druc Peter Wooldridge A. Krishnamurthy S. Sarkar Aditya Balu 2 0 0 20 Feb 2023
Batch Normalization Explained Randall Balestriero Richard G. Baraniuk AAML 13 16 0 29 Sep 2022
Time Series Simulation by Conditional Generative Adversarial Net Rao Fu Jie Chen Shutian Zeng Yiping Zhuang Agus Sudjianto AI4TS OOD GAN 9 47 0 25 Apr 2019
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 163 596 0 22 Sep 2016
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding V. Papyan Yaniv Romano Michael Elad 48 283 0 27 Jul 2016
Piecewise convexity of artificial neural networks Blaine Rister Daniel L Rubin AAML ODL 16 31 0 17 Jul 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 247 5,813 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 245 9,042 0 06 Jun 2015