Backpropagation through the Void: Optimizing control variates for black-box gradient estimation

31 October 2017

Papers citing "Backpropagation through the Void: Optimizing control variates for black-box gradient estimation"

50 / 204 papers shown

Title
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition Randy Ardywibowo Shahin Boluki Zhangyang Wang Bobak J. Mortazavi Shuai Huang Xiaoning Qian 14 2 0 31 Mar 2022
Gradient Estimation with Discrete Stein Operators Jiaxin Shi Yuhao Zhou Jessica Hwang Michalis K. Titsias Lester W. Mackey 33 22 0 19 Feb 2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo Sébastien M. R. Arnold P. LÉcuyer Liyu Chen Yi-fan Chen Fei Sha OffRL 37 4 0 16 Feb 2022
Deep invariant networks with differentiable augmentation layers Cédric Rommel Thomas Moreau Alexandre Gramfort OOD 27 8 0 04 Feb 2022
Zeroth-Order Actor-Critic: An Evolutionary Framework for Sequential Decision Problems Yuheng Lei Jianyu Chen Guojian Zhan Tao Zhang Jiangtao Li Jianyu Chen Shengbo Eben Li Sifa Zheng OffRL 23 2 0 29 Jan 2022
SABLAS: Learning Safe Control for Black-box Dynamical Systems Zengyi Qin Dawei Sun Chuchu Fan 26 43 0 06 Jan 2022
Programming with Neural Surrogates of Programs Alex Renda Yi Ding Michael Carbin 16 2 0 12 Dec 2021
Learning Generalized Gumbel-max Causal Mechanisms Guy Lorberbom Daniel D. Johnson Chris J. Maddison Daniel Tarlow Tamir Hazan CML 14 20 0 11 Nov 2021
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models Michalis K. Titsias Jiaxin Shi BDL DRL 28 5 0 09 Nov 2021
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces Kirill Struminsky Artyom Gadetsky D. Rakitin Danil Karpushkin Dmitry Vetrov BDL 27 9 0 28 Oct 2021
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator Alek Dimitriev Mingyuan Zhou 14 7 0 26 Oct 2021
Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units K. Young 31 0 0 14 Oct 2021
Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators Alexander Shekhovtsov MQ 31 4 0 07 Oct 2021
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests Victor Chernozhukov Whitney Newey Victor Quintas-Martinez Vasilis Syrgkanis CML 13 36 0 06 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning Iris A. M. Huijben W. Kool Max B. Paulus Ruud J. G. van Sloun 28 94 0 04 Oct 2021
Smooth Normalizing Flows Jonas Köhler Andreas Krämer Frank Noé 29 53 0 01 Oct 2021
Self-Conditioned Probabilistic Learning of Video Rescaling Yuan Tian Guo Lu Xiongkuo Min Zhaohui Che Guangtao Zhai G. Guo Zhiyong Gao 30 26 0 24 Jul 2021
An overview of mixing augmentation methods and augmentation strategies Dominik Lewy Jacek Mańdziuk 25 61 0 21 Jul 2021
Coordinate-wise Control Variates for Deep Policy Gradients Yuanyi Zhong Yuanshuo Zhou Jian-wei Peng BDL 21 1 0 11 Jul 2021
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface T. Le K. M. Collins Luke B. Hewitt Kevin Ellis N. Siddharth S. Gershman J. Tenenbaum 122 5 0 04 Jul 2021
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals Cédric Rommel Thomas Moreau Joseph Paillard Alexandre Gramfort 19 37 0 25 Jun 2021
Coupled Gradient Estimators for Discrete Latent Variables Zhe Dong A. Mnih George Tucker BDL 38 13 0 15 Jun 2021
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures Yashas Annadani Jonas Rothfuss Alexandre Lacoste Nino Scherrer Anirudh Goyal Yoshua Bengio Stefan Bauer BDL CML 32 48 0 14 Jun 2021
Multi-Facet Clustering Variational Autoencoders Fabian Falck Haoting Zhang M. Willetts G. Nicholson C. Yau Chris Holmes DRL 28 40 0 09 Jun 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Mathias Niepert Pasquale Minervini Luca Franceschi 32 81 0 03 Jun 2021
A unified view of likelihood ratio and reparameterization gradients Paavo Parmas Masashi Sugiyama 20 9 0 31 May 2021
ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary Variables Alek Dimitriev Mingyuan Zhou 21 12 0 28 May 2021
Direct Differentiable Augmentation Search Aoming Liu Zehao Huang Zhiwu Huang Naiyan Wang 33 33 0 09 Apr 2021
Storchastic: A Framework for General Stochastic Automatic Differentiation Emile van Krieken Jakub M. Tomczak A. T. Teije ODL OffRL 31 15 0 01 Apr 2021
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning Hiroki Furuta Tadashi Kozuno T. Matsushima Y. Matsuo S. Gu 18 14 0 31 Mar 2021
Post-Processing of MCMC Leah F. South M. Riabiz Onur Teymur Chris J. Oates 22 17 0 30 Mar 2021
Modeling Graph Node Correlations with Neighbor Mixture Models Linfeng Liu Michael Hughes Liping Liu 31 0 0 29 Mar 2021
Model-free Policy Learning with Reward Gradients Qingfeng Lan Samuele Tosatto Homayoon Farrahi Rupam Mahmood 19 6 0 09 Mar 2021
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search Kartik Hegde Po-An Tsai Sitao Huang Vikas Chandra A. Parashar Christopher W. Fletcher 26 92 0 02 Mar 2021
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs Thomas Spooner N. Vadori Sumitra Ganesh 30 7 0 20 Feb 2021
Latent Template Induction with Gumbel-CRFs Yao Fu Chuanqi Tan Bin Bi Mosha Chen Yansong Feng Alexander M. Rush BDL 13 12 0 29 Nov 2020
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents E. Guiraud Jakob Drefs Jörg Lücke DRL 40 3 0 27 Nov 2020
TaylorGAN: Neighbor-Augmented Policy Update for Sample-Efficient Natural Language Generation Chun-Hsing Lin Siang-Ruei Wu Hung-yi Lee Yun-Nung Chen LLMAG 10 3 0 27 Nov 2020
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration H. Dai Rishabh Singh Bo Dai Charles Sutton Dale Schuurmans 27 27 0 10 Nov 2020
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 138 48 0 20 Oct 2020
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator Max B. Paulus Chris J. Maddison Andreas Krause BDL 42 38 0 09 Oct 2020
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates Alex Renda Yishen Chen Charith Mendis Michael Carbin 8 35 0 08 Oct 2020
Beyond variance reduction: Understanding the true impact of baselines on policy optimization Wesley Chung Valentin Thomas Marlos C. Machado Nicolas Le Roux OffRL 14 22 0 31 Aug 2020
Natural Reweighted Wake-Sleep Csongor-Huba Várady Riccardo Volpi Luigi Malagò Nihat Ay BDL 21 0 0 15 Aug 2020
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds Valentin Liévin Andrea Dittadi Anders Christensen Ole Winther DRL 30 6 0 05 Aug 2020
Foveation for Segmentation of Ultra-High Resolution Images Chen Jin Ryutaro Tanno Moucheng Xu T. Mertzanidou Daniel C. Alexander AI4TS 19 4 0 29 Jul 2020
Approximation Based Variance Reduction for Reparameterization Gradients Tomas Geffner Justin Domke BDL DRL 23 10 0 29 Jul 2020
Relaxed-Responsibility Hierarchical Discrete VAEs M. Willetts Xenia Miscouridou Stephen J. Roberts Chris Holmes BDL DRL 30 5 0 14 Jul 2020
NVAE: A Deep Hierarchical Variational Autoencoder Arash Vahdat Jan Kautz BDL 15 894 0 08 Jul 2020
Learning to learn generative programs with Memoised Wake-Sleep Luke B. Hewitt T. Le J. Tenenbaum CLL 20 26 0 06 Jul 2020