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A simple and efficient architecture for trainable activation functions

8 February 2019

Papers citing "A simple and efficient architecture for trainable activation functions"

21 / 21 papers shown

Title
Towards Identifiability of Interventional Stochastic Differential Equations Aaron Zweig Zaikang Lin Elham Azizi David A. Knowles 62 1 0 21 May 2025
Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks L. R. Sütfeld Flemming Brieger Holger Finger S. Füllhase G. Pipa 55 29 0 26 Jun 2018
Comparison of non-linear activation functions for deep neural networks on MNIST classification task Dabal Pedamonti 51 187 0 08 Apr 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,928 0 25 Aug 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 486 2,520 0 08 Jun 2017
Activation Ensembles for Deep Neural Networks Mark Harmon Diego Klabjan 174 35 0 24 Feb 2017
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks Ludovic Trottier Philippe Giguère B. Chaib-draa 81 200 0 30 May 2016
Learning activation functions from data using cubic spline interpolation Simone Scardapane M. Scarpiniti Danilo Comminiello A. Uncini 50 29 0 18 May 2016
A single hidden layer feedforward network with only one neuron in the hidden layer can approximate any univariate function Namig J. Guliyev V. Ismailov 36 79 0 31 Dec 2015
Deep Learning with S-shaped Rectified Linear Activation Units Xiaojie Jin Chunyan Xu Jiashi Feng Yunchao Wei Junjun Xiong Shuicheng Yan 412 217 0 22 Dec 2015
The Power of Depth for Feedforward Neural Networks Ronen Eldan Ohad Shamir 224 732 0 12 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 307 5,536 0 23 Nov 2015
Neural Network with Unbounded Activation Functions is Universal Approximator Sho Sonoda Noboru Murata 70 336 0 14 May 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 347 18,654 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Learning Activation Functions to Improve Deep Neural Networks Forest Agostinelli Matthew Hoffman Peter Sadowski Pierre Baldi ODL 230 475 0 21 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 238 8,353 0 06 Nov 2014
An ensemble-based system for automatic screening of diabetic retinopathy B. Antal András Hajdu 95 237 0 30 Oct 2014
Zero-bias autoencoders and the benefits of co-adapting features K. Konda Roland Memisevic David M. Krueger AI4CE 90 92 0 13 Feb 2014
Network In Network Min Lin Qiang Chen Shuicheng Yan 297 6,285 0 16 Dec 2013
Maxout Networks Ian Goodfellow David Warde-Farley M. Berk Mirza Aaron Courville Yoshua Bengio OOD 262 2,179 0 18 Feb 2013