Learning Discrete Weights Using the Local Reparameterization Trick

21 October 2017

Papers citing "Learning Discrete Weights Using the Local Reparameterization Trick"

26 / 26 papers shown

Title
Efficient Learning of Discrete-Continuous Computation Graphs David Friede Mathias Niepert 13 3 0 26 Jul 2023
Learning Discrete Weights and Activations Using the Local Reparameterization Trick G. Berger Aviv Navon Ethan Fetaya MQ 22 0 0 04 Jul 2023
Hyperspherical Quantization: Toward Smaller and More Accurate Models Dan Liu X. Chen Chen-li Ma Xue Liu MQ 30 3 0 24 Dec 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 25 11 0 11 Aug 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 65 75 0 28 May 2022
Nonlocal optimization of binary neural networks Amir Khoshaman Giuseppe Castiglione C. Srinivasa 18 0 0 05 Apr 2022
Signing the Supermask: Keep, Hide, Invert Nils Koster O. Grothe Achim Rettinger 31 10 0 31 Jan 2022
Resource-efficient Deep Neural Networks for Automotive Radar Interference Mitigation J. Rock Wolfgang Roth Máté Tóth Paul Meissner Franz Pernkopf 19 43 0 25 Jan 2022
Federated Learning via Plurality Vote Kai Yue Richeng Jin Chau-Wai Wong H. Dai FedML 24 8 0 06 Oct 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 26 6 0 01 Oct 2021
Differentiable Model Compression via Pseudo Quantization Noise Alexandre Défossez Yossi Adi Gabriel Synnaeve DiffM MQ 18 47 0 20 Apr 2021
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks Julieta Martinez Jashan Shewakramani Ting Liu Ioan Andrei Bârsan Wenyuan Zeng R. Urtasun MQ 18 30 0 29 Oct 2020
Quantum Deformed Neural Networks Roberto Bondesan Max Welling AI4CE 15 4 0 21 Oct 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 136 48 0 20 Oct 2020
Training Binary Neural Networks using the Bayesian Learning Rule Xiangming Meng Roman Bachmann Mohammad Emtiyaz Khan BDL MQ 30 40 0 25 Feb 2020
Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth Günther Schindler Lukas Pfeifenberger Robert Peharz Sebastian Tschiatschek Holger Fröning Franz Pernkopf Zoubin Ghahramani 31 47 0 07 Jan 2020
Adaptive Loss-aware Quantization for Multi-bit Networks Zhongnan Qu Zimu Zhou Yun Cheng Lothar Thiele MQ 33 53 0 18 Dec 2019
And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock Armand Joulin Rémi Gribonval Benjamin Graham Hervé Jégou MQ 31 149 0 12 Jul 2019
Weight Normalization based Quantization for Deep Neural Network Compression Wenhong Cai Wu-Jun Li 16 14 0 01 Jul 2019
Progressive Stochastic Binarization of Deep Networks David Hartmann Michael Wand MQ 12 1 0 03 Apr 2019
Low-bit Quantization of Neural Networks for Efficient Inference Yoni Choukroun Eli Kravchik Fan Yang P. Kisilev MQ 16 355 0 18 Feb 2019
Entropy-Constrained Training of Deep Neural Networks Simon Wiedemann Arturo Marbán K. Müller Wojciech Samek 20 27 0 18 Dec 2018
Relaxed Quantization for Discretized Neural Networks Christos Louizos M. Reisser Tijmen Blankevoort E. Gavves Max Welling MQ 30 131 0 03 Oct 2018
Probabilistic Binary Neural Networks Jorn W. T. Peters Max Welling BDL UQCV MQ 19 50 0 10 Sep 2018
A Survey on Methods and Theories of Quantized Neural Networks Yunhui Guo MQ 29 230 0 13 Aug 2018
Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing Amir Rosenfeld John K. Tsotsos MLT 29 51 0 02 Feb 2018