Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

15 August 2013

Aaron Courville

Papers citing "Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation"

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Title
Deep-learning-based Optimization of the Under-sampling Pattern in MRI C. D. Bahadir Alan Q. Wang Adrian Dalca M. Sabuncu 30 9 0 26 Jul 2019
Notes on Latent Structure Models and SPIGOT André F. T. Martins Vlad Niculae BDL 14 0 0 24 Jul 2019
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Large Memory Layers with Product Keys Guillaume Lample Alexandre Sablayrolles MarcÁurelio Ranzato Ludovic Denoyer Hervé Jégou MoE 33 131 0 10 Jul 2019
Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization Dimitrios Stamoulis Ruizhou Ding Di Wang Dimitrios Lymberopoulos B. Priyantha Jie Liu Diana Marculescu 12 33 0 01 Jul 2019
Compression of Acoustic Event Detection Models With Quantized Distillation Bowen Shi Ming Sun Chieh-Chi Kao Viktor Rozgic Spyros Matsoukas Chao Wang 22 13 0 01 Jul 2019
Binary Stochastic Representations for Large Multi-class Classification Thomas Gerald Aurélia Léon Nicolas Baskiotis Ludovic Denoyer 16 3 0 24 Jun 2019
Back to Simplicity: How to Train Accurate BNNs from Scratch? Joseph Bethge Haojin Yang Marvin Bornstein Christoph Meinel AAML MQ 25 58 0 19 Jun 2019
Joint Learning of Geometric and Probabilistic Constellation Shaping Maximilian Stark Fayçal Ait Aoudia J. Hoydis 36 81 0 18 Jun 2019
Structured Pruning of Recurrent Neural Networks through Neuron Selection Liangjiang Wen Xuanyang Zhang Haoli Bai Zenglin Xu 18 38 0 17 Jun 2019
Conditional Computation for Continual Learning Min Lin Jie Fu Yoshua Bengio CLL 34 10 0 16 Jun 2019
Scalable Model Compression by Entropy Penalized Reparameterization Deniz Oktay Johannes Ballé Saurabh Singh Abhinav Shrivastava 27 42 0 15 Jun 2019
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks Ahmed T. Elthakeb Prannoy Pilligundla Alex Cloninger H. Esmaeilzadeh MQ 26 8 0 14 Jun 2019
Parameterized Structured Pruning for Deep Neural Networks Günther Schindler Wolfgang Roth Franz Pernkopf Holger Froening 26 6 0 12 Jun 2019
Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling Duanshun Li Jing Liu Noseong Park Dongeun Lee Giridhar Kaushik Ramachandran Ali Seyed Mazloom Kookjin Lee Chen Feng Vadim Sokolov R. Ganesan 28 0 0 11 Jun 2019
Self-Supervised Exploration via Disagreement Deepak Pathak Dhiraj Gandhi Abhinav Gupta SSL 35 375 0 10 Jun 2019
Fighting Quantization Bias With Bias Alexander Finkelstein Uri Almog Mark Grobman MQ 28 56 0 07 Jun 2019
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization K. Helwegen James Widdicombe Lukas Geiger Zechun Liu K. Cheng Roeland Nusselder MQ 27 110 0 05 Jun 2019
Interpretable Neural Network Decoupling Yuchao Li Rongrong Ji Shaohui Lin Baochang Zhang Chenqian Yan Yongjian Wu Feiyue Huang Ling Shao 37 2 0 04 Jun 2019
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization Ikuro Sato Kohta Ishikawa Guoqing Liu Masayuki Tanaka 25 5 0 04 Jun 2019
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds Bo Yang Jianan Wang R. Clark Qingyong Hu Sen Wang Andrew Markham A. Trigoni 3DPC 41 325 0 04 Jun 2019
Relation Embedding with Dihedral Group in Knowledge Graph Canran Xu Ruijiang Li 16 73 0 03 Jun 2019
Unsupervised Neural Generative Semantic Hashing Casper Hansen Christian B. Hansen J. Simonsen Stephen Alstrup Christina Lioma 27 22 0 03 Jun 2019
Discovering Neural Wirings Mitchell Wortsman Ali Farhadi Mohammad Rastegari AI4CE 16 120 0 03 Jun 2019
Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1 Qigong Sun Fanhua Shang Kan Yang Xiufang Li Yan Ren L. Jiao MQ 46 12 0 31 May 2019
Deep Learning for Distributed Optimization: Applications to Wireless Resource Management Hoon Lee Sang Hyun Lee Tony Q.S. Quek 23 92 0 31 May 2019
Toward Runtime-Throttleable Neural Networks Jesse Hostetler 29 2 0 30 May 2019
Quantization Loss Re-Learning Method Kunping Li MQ 14 1 0 30 May 2019
Learning Navigation Subroutines from Egocentric Videos Ashish Kumar Saurabh Gupta Jitendra Malik SSL EgoV 25 13 0 29 May 2019
EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction Diane Bouchacourt Ludovic Denoyer FAtt 29 21 0 28 May 2019
Progressive Learning of Low-Precision Networks Zhengguang Zhou Wen-gang Zhou Xutao Lv Xuan Huang Xiaoyu Wang Houqiang Li MQ 44 11 0 28 May 2019
Inference with Hybrid Bio-hardware Neural Networks Yuan Zeng Zubayer Ibne Ferdous Weixian Zhang Mufan Xu Anlan Yu Drew Patel Xiaochen Guo Y. Berdichevsky Zhiyuan Yan 10 4 0 28 May 2019
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization Ting-Hao 'Kenneth' Huang Gehui Shen Zhihong Deng VLM AI4TS 25 22 0 28 May 2019
Mixed Precision DNNs: All you need is a good parametrization Stefan Uhlich Lukas Mauch Fabien Cardinaux K. Yoshiyama Javier Alonso García Stephen Tiedemann Thomas Kemp Akira Nakamura MQ 27 38 0 27 May 2019
ProbAct: A Probabilistic Activation Function for Deep Neural Networks Kumar Shridhar JoonHo Lee Hideaki Hayashi Purvanshi Mehta Brian Kenji Iwana Seokjun Kang S. Uchida Sheraz Ahmed Andreas Dengel DiffM AAML 19 32 0 26 May 2019
Additive Noise Annealing and Approximation Properties of Quantized Neural Networks Matteo Spallanzani Lukas Cavigelli G. P. Leonardi Marko Bertogna Luca Benini 19 15 0 24 May 2019
Discrete Flows: Invertible Generative Models of Discrete Data Dustin Tran Keyon Vafa Kumar Krishna Agrawal Laurent Dinh Ben Poole DRL 24 114 0 24 May 2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks Gaël Letarte Pascal Germain Benjamin Guedj Franccois Laviolette MQ AI4CE UQCV 28 54 0 24 May 2019
Interpretable Neural Predictions with Differentiable Binary Variables Jasmijn Bastings Wilker Aziz Ivan Titov 32 212 0 20 May 2019
Integer Discrete Flows and Lossless Compression Emiel Hoogeboom Jorn W. T. Peters Rianne van den Berg Max Welling 30 158 0 17 May 2019
Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruning Sara Elkerdawy Hong Zhang Nilanjan Ray MDE VLM 21 20 0 13 May 2019
Improving Discrete Latent Representations With Differentiable Approximation Bridges Jason Ramapuram Russ Webb DRL 19 9 0 09 May 2019
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables Mingzhang Yin Yuguang Yue Mingyuan Zhou 22 23 0 04 May 2019
Compression of Acoustic Event Detection Models with Low-rank Matrix Factorization and Quantization Training Bowen Shi Ming Sun Chieh-Chi Kao Viktor Rozgic Spyros Matsoukas Chao Wang 29 14 0 02 May 2019
PR Product: A Substitute for Inner Product in Neural Networks Zhennan Wang Wenbin Zou Chen Xu 28 6 0 30 Apr 2019
Incorporating Symbolic Sequential Modeling for Speech Enhancement Chien-Feng Liao Yu Tsao Xugang Lu Hisashi Kawai 27 18 0 30 Apr 2019
Memory-Augmented Temporal Dynamic Learning for Action Recognition Yuan. Yuan Dong Wang Qi. Wang 30 13 0 30 Apr 2019
SEALion: a Framework for Neural Network Inference on Encrypted Data Tim van Elsloo Giorgio Patrini Hamish Ivey-Law FedML 30 42 0 29 Apr 2019
Routing Networks and the Challenges of Modular and Compositional Computation Clemens Rosenbaum Ignacio Cases Matthew D Riemer Tim Klinger 40 78 0 29 Apr 2019
Deep Neuroevolution of Recurrent and Discrete World Models S. Risi Kenneth O. Stanley OCL 22 53 0 28 Apr 2019