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Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units

16 March 2016

Papers citing "Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units"

21 / 171 papers shown

Title
Dual Rectified Linear Units (DReLUs): A Replacement for Tanh Activation Functions in Quasi-Recurrent Neural Networks Fréderic Godin Jonas Degrave J. Dambre W. D. Neve MU 36 47 0 25 Jul 2017
Kafnets: kernel-based non-parametric activation functions for neural networks Simone Scardapane S. Van Vaerenbergh Simone Totaro A. Uncini 36 12 0 13 Jul 2017
Towards lightweight convolutional neural networks for object detection Dmitriy Anisimov T. Khanova ObjD 84 40 0 05 Jul 2017
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems J. C. Ye Yoseob Han Eunju Cha 114 16 0 03 Jul 2017
A Useful Motif for Flexible Task Learning in an Embodied Two-Dimensional Visual Environment Kevin T. Feigelis Daniel L. K. Yamins 34 0 0 22 Jun 2017
DiracNets: Training Very Deep Neural Networks Without Skip-Connections Sergey Zagoruyko N. Komodakis UQCV OOD 79 119 0 01 Jun 2017
Towards Understanding the Invertibility of Convolutional Neural Networks A. Gilbert Yi Zhang Kibok Lee Y. Zhang Honglak Lee 89 64 0 24 May 2017
Probabilistic Image Colorization Amelie Royer Alexander Kolesnikov Christoph H. Lampert 68 44 0 11 May 2017
The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning A. Gruslys Will Dabney M. G. Azar Bilal Piot Marc G. Bellemare Rémi Munos 76 58 0 15 Apr 2017
All You Need is Beyond a Good Init: Exploring Better Solution for Training Extremely Deep Convolutional Neural Networks with Orthonormality and Modulation Di Xie Jiang Xiong Shiliang Pu 147 183 0 06 Mar 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question? David Balduzzi Marcus Frean Lennox Leary J. P. Lewis Kurt Wan-Duo Ma Brian McWilliams ODL 75 406 0 28 Feb 2017
Steerable CNNs Taco S. Cohen Max Welling BDL 147 499 0 27 Dec 2016
PVANet: Lightweight Deep Neural Networks for Real-time Object Detection Sanghoon Hong Byungseok Roh Kye-Hyeon Kim Yeongjae Cheon Minje Park ObjD 77 83 0 23 Nov 2016
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks David Balduzzi Brian McWilliams T. Butler-Yeoman 74 29 0 07 Nov 2016
Doubly Convolutional Neural Networks Shuangfei Zhai Yu Cheng Weining Lu Zhongfei Zhang OOD 3DV 71 63 0 30 Oct 2016
Maxmin convolutional neural networks for image classification Michael Blot Matthieu Cord Nicolas Thome 44 45 0 25 Oct 2016
PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection Kye-Hyeon Kim Sanghoon Hong Byungseok Roh Yeongjae Cheon Minje Park ObjD VLM 91 208 0 29 Aug 2016
Softplus Regressions and Convex Polytopes Mingyuan Zhou 78 16 0 23 Aug 2016
Every Filter Extracts A Specific Texture In Convolutional Neural Networks Zhiqiang Xia Ce Zhu Z. Wang Qi Guo Yipeng Liu FAtt 42 2 0 15 Aug 2016
Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation D. L. Richmond Dagmar Kainmüller M. Yang E. Myers Carsten Rother SSeg 135 14 0 27 Jul 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 553 43,400 0 11 Feb 2015