Gradient Estimation Using Stochastic Computation Graphs

17 June 2015

Pieter Abbeel

Papers citing "Gradient Estimation Using Stochastic Computation Graphs"

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Title
Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Eliot Xing Vernon Luk Jean Oh 84 0 0 16 Dec 2024
Generating Transferable Adversarial Simulation Scenarios for Self-Driving via Neural Rendering Yasasa Abeysirigoonawardena Kevin Xie Chuhan Chen Salar Hosseini Ruiting Chen Ruiqi Wang Florian Shkurti 36 2 0 27 Sep 2023
Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics Michael Kagan Lukas Heinrich 32 9 0 31 Aug 2023
Efficient Learning of Discrete-Continuous Computation Graphs David Friede Mathias Niepert 13 3 0 26 Jul 2023
Learning to Select Camera Views: Efficient Multiview Understanding at Few Glances Yunzhong Hou Stephen Gould Liang Zheng 22 1 0 10 Mar 2023
A Tutorial on Parametric Variational Inference Jens Sjölund BDL 30 6 0 03 Jan 2023
Efficient Transformers with Dynamic Token Pooling Piotr Nawrot J. Chorowski Adrian Lañcucki Edoardo Ponti 22 42 0 17 Nov 2022
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya Moritz Schauer Frank Schafer Chris Rackauckas 23 34 0 16 Oct 2022
A Variational Perspective on Generative Flow Networks Heiko Zimmermann Fredrik Lindsten Jan-Willem van de Meent C. A. Naesseth 22 32 0 14 Oct 2022
Ensemble Reinforcement Learning in Continuous Spaces -- A Hierarchical Multi-Step Approach for Policy Training Gang Chen Victoria Huang OffRL 40 0 0 29 Sep 2022
Deep Structural Causal Shape Models Rajat Rasal Daniel Coelho De Castro Nick Pawlowski Ben Glocker 3DV MedIm 36 12 0 23 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 24 9 0 22 Aug 2022
Drawing out of Distribution with Neuro-Symbolic Generative Models Yi-Chuan Liang J. Tenenbaum T. Le N. Siddharth 23 7 0 03 Jun 2022
Sparse Graph Learning from Spatiotemporal Time Series Andrea Cini Daniele Zambon Cesare Alippi CML AI4TS 43 18 0 26 May 2022
Sample-efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs Siow Meng Low Akshat Kumar Scott Sanner 19 3 0 23 Mar 2022
Safe Neurosymbolic Learning with Differentiable Symbolic Execution Chenxi Yang Swarat Chaudhuri 27 9 0 15 Mar 2022
Consistent Dropout for Policy Gradient Reinforcement Learning Matthew J. Hausknecht Nolan Wagener OffRL 24 10 0 23 Feb 2022
C2N: Practical Generative Noise Modeling for Real-World Denoising Geonwoon Jang Wooseok Lee Sanghyun Son Kyoung Mu Lee DiffM 33 78 0 19 Feb 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
Deep invariant networks with differentiable augmentation layers Cédric Rommel Thomas Moreau Alexandre Gramfort OOD 27 8 0 04 Feb 2022
Do Differentiable Simulators Give Better Policy Gradients? H.J. Terry Suh Max Simchowitz Kaipeng Zhang Russ Tedrake 32 95 0 02 Feb 2022
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning Haichao Zhang Wei-ping Xu Haonan Yu 38 10 0 24 Jan 2022
PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation Gopal Sharma Bidya Dash Aruni RoyChowdhury Matheus Gadelha Marios Loizou Liangliang Cao Rui Wang Erik Learned-Miller Subhransu Maji E. Kalogerakis 3DPC 21 13 0 27 Dec 2021
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 27 67 0 27 Dec 2021
Gradients are Not All You Need Luke Metz C. Freeman S. Schoenholz Tal Kachman 30 93 0 10 Nov 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 29 20 0 21 Jun 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank Wood 28 19 0 18 Jun 2021
Characterizing the Gap Between Actor-Critic and Policy Gradient Junfeng Wen Saurabh Kumar Ramki Gummadi Dale Schuurmans 31 15 0 13 Jun 2021
Parallel Attention Network with Sequence Matching for Video Grounding Hao Zhang Aixin Sun Wei Jing Liangli Zhen Qiufeng Wang Rick Siow Mong Goh 18 40 0 18 May 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
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times Omer Dahary M. Jacoby A. Bronstein 19 5 0 08 Dec 2020
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents E. Guiraud Jakob Drefs Jörg Lücke DRL 40 3 0 27 Nov 2020
Rescuing neural spike train models from bad MLE Diego M. Arribas Yuan Zhao Il Memming Park 37 8 0 23 Oct 2020
Factor Graph Grammars David Chiang Darcey Riley LRM 21 10 0 22 Oct 2020
Model-Augmented Actor-Critic: Backpropagating through Paths I. Clavera Yao Fu Pieter Abbeel 44 87 0 16 May 2020
On the Spontaneous Emergence of Discrete and Compositional Signals Nur Lan Emmanuel Chemla Shane Steinert-Threlkeld LRM 16 8 0 30 Apr 2020
Information-Theoretic Lower Bounds for Zero-Order Stochastic Gradient Estimation Abdulrahman Alabdulkareem Jean Honorio 6 2 0 31 Mar 2020
ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds Gopal Sharma Difan Liu Subhransu Maji E. Kalogerakis S. Chaudhuri Radomír Mvech 3DPC 24 138 0 26 Mar 2020
Better Captioning with Sequence-Level Exploration Jia Chen Qin Jin 37 12 0 08 Mar 2020
Visual Camera Re-Localization from RGB and RGB-D Images Using DSAC Eric Brachmann Carsten Rother 41 220 0 27 Feb 2020
Estimating Gradients for Discrete Random Variables by Sampling without Replacement W. Kool H. V. Hoof Max Welling BDL 31 49 0 14 Feb 2020
All-Action Policy Gradient Methods: A Numerical Integration Approach Benjamin Petit Loren Amdahl-Culleton Yao Liu Jimmy T.H. Smith Pierre-Luc Bacon 24 9 0 21 Oct 2019
Deep clustering with concrete k-means Boyan Gao Yongxin Yang Henry Gouk Timothy M. Hospedales 13 16 0 17 Oct 2019
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning Gregory Farquhar Shimon Whiteson Jakob N. Foerster 13 18 0 23 Sep 2019
Causal Modeling for Fairness in Dynamical Systems Elliot Creager David Madras T. Pitassi R. Zemel 13 67 0 18 Sep 2019
Neural Text Summarization: A Critical Evaluation Wojciech Kry'sciñski N. Keskar Bryan McCann Caiming Xiong R. Socher 22 361 0 23 Aug 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 45 397 0 25 Jun 2019
Learning Belief Representations for Imitation Learning in POMDPs Tanmay Gangwani Joel Lehman Qiang Liu Jian Peng 24 36 0 22 Jun 2019
Meta-Learning via Learned Loss Sarah Bechtle Artem Molchanov Yevgen Chebotar Edward Grefenstette Ludovic Righetti Gaurav Sukhatme Franziska Meier 20 110 0 12 Jun 2019