Estimating or Propagating Gradients Through Stochastic Neurons

14 May 2013

Papers citing "Estimating or Propagating Gradients Through Stochastic Neurons"

27 / 27 papers shown

Title
Optimizing Deep Neural Networks using Safety-Guided Self Compression Mohammad Zbeeb Mariam Salman Mohammad Bazzi Ammar Mohanna 28 0 0 01 May 2025
Opportunities and Challenges of Generative-AI in Finance Akshar Prabhu Desai Ganesh Satish Mallya Mohammad Luqman Tejasvi Ravi Nithya Kota Pranjul Yadav AIFin 42 2 0 21 Oct 2024
Model-based Programming: Redefining the Atomic Unit of Programming for the Deep Learning Era Meng-Jie Zheng 18 0 0 12 May 2023
Hyperspherical Quantization: Toward Smaller and More Accurate Models Dan Liu X. Chen Chen Ma Xue Liu MQ 30 3 0 24 Dec 2022
Latent Iterative Refinement for Modular Source Separation Dimitrios Bralios Efthymios Tzinis G. Wichern Paris Smaragdis Jonathan Le Roux BDL 33 5 0 22 Nov 2022
Learning to Express in Knowledge-Grounded Conversation Xueliang Zhao Tingchen Fu Chongyang Tao Wei Wu Dongyan Zhao Rui Yan 25 6 0 12 Apr 2022
Bit-wise Training of Neural Network Weights Cristian Ivan MQ 18 0 0 19 Feb 2022
ReCU: Reviving the Dead Weights in Binary Neural Networks Zihan Xu Mingbao Lin Jianzhuang Liu Jie Chen Ling Shao Yue Gao Yonghong Tian Rongrong Ji MQ 24 81 0 23 Mar 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey Tailin Liang C. Glossner Lei Wang Shaobo Shi Xiaotong Zhang MQ 150 675 0 24 Jan 2021
Training highly effective connectivities within neural networks with randomly initialized, fixed weights Cristian Ivan Razvan V. Florian 19 4 0 30 Jun 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán Umang Bhatt T. Adel Adrian Weller José Miguel Hernández-Lobato UQCV BDL 40 111 0 11 Jun 2020
Robust Training of Vector Quantized Bottleneck Models A. Lancucki J. Chorowski Guillaume Sanchez R. Marxer Nanxin Chen Hans J. G. A. Dolfing Sameer Khurana Tanel Alumäe Antoine Laurent 29 58 0 18 May 2020
DeepLPF: Deep Local Parametric Filters for Image Enhancement Sean J. Moran Pierre Marza Jingyu Sun Sarah Parisot Greg Slabaugh 25 192 0 31 Mar 2020
PRNet: Self-Supervised Learning for Partial-to-Partial Registration Yue Wang Justin Solomon SSL 3DPC 19 379 0 27 Oct 2019
DFTerNet: Towards 2-bit Dynamic Fusion Networks for Accurate Human Activity Recognition Zhan Yang Osolo Ian Raymond Chengyuan Zhang Ying Wan J. Long CVBM 39 36 0 31 Jul 2018
Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation Binghui Chen Weihong Deng Junping Du 25 125 0 12 Aug 2017
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations Itay Hubara Matthieu Courbariaux Daniel Soudry Ran El-Yaniv Yoshua Bengio MQ 42 1,842 0 22 Sep 2016
Mollifying Networks Çağlar Gülçehre Marcin Moczulski Francesco Visin Yoshua Bengio 23 46 0 17 Aug 2016
Relative Natural Gradient for Learning Large Complex Models Ke Sun Frank Nielsen 29 5 0 20 Jun 2016
Noisy Activation Functions Çağlar Gülçehre Marcin Moczulski Misha Denil Yoshua Bengio 9 283 0 01 Mar 2016
Binarized Neural Networks Itay Hubara Daniel Soudry Ran El-Yaniv MQ 58 1,351 0 08 Feb 2016
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 49 1,493 0 08 Jun 2015
Difference Target Propagation Dong-Hyun Lee Saizheng Zhang Asja Fischer Yoshua Bengio AAML 23 346 0 23 Dec 2014
Techniques for Learning Binary Stochastic Feedforward Neural Networks T. Raiko Mathias Berglund Guillaume Alain Laurent Dinh BDL 57 126 0 11 Jun 2014
Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio Eric Thibodeau-Laufer Guillaume Alain J. Yosinski BDL 50 396 0 05 Jun 2013
Deep Learning of Representations: Looking Forward Yoshua Bengio 57 680 0 02 May 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012