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Adaptive importance sampling for control and inference

7 May 2015

Papers citing "Adaptive importance sampling for control and inference"

36 / 36 papers shown

Title
Trajectory Planning with Signal Temporal Logic Costs using Deterministic Path Integral Optimization Patrick Halder Hannes Homburger Lothar Kiltz Johannes Reuter Matthias Althoff 64 1 0 03 Mar 2025
A Taxonomy of Loss Functions for Stochastic Optimal Control Carles Domingo-Enrich 75 4 0 01 Oct 2024
Robust Pushing: Exploiting Quasi-static Belief Dynamics and Contact-informed Optimization Julius Jankowski Lara Brudermüller Nick Hawes Sylvain Calinon 84 3 0 03 Apr 2024
Stochastic Optimal Control Matching Carles Domingo-Enrich Jiequn Han Brandon Amos Joan Bruna Ricky T. Q. Chen DiffM 116 10 0 04 Dec 2023
Variational Inference for SDEs Driven by Fractional Noise Rembert Daems Manfred Opper Guillaume Crevecoeur Tolga Birdal 99 6 0 19 Oct 2023
Generalized Schrödinger Bridge Matching Guan-Horng Liu Y. Lipman Maximilian Nickel Brian Karrer Evangelos A. Theodorou Ricky T. Q. Chen DiffM 94 19 0 03 Oct 2023
Recent Advances in Path Integral Control for Trajectory Optimization: An Overview in Theoretical and Algorithmic Perspectives Muhammad Kazim JunGee Hong Min-Gyeom Kim Kwang-Ki K. Kim 74 19 0 22 Sep 2023
Diffusion Schrödinger Bridges for Bayesian Computation J. Heng Valentin De Bortoli Arnaud Doucet DiffM 53 3 0 27 Aug 2023
Denoising Diffusion Samplers Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 67 91 0 27 Feb 2023
Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes Joe Watson Jan Peters 88 16 0 07 Oct 2022
Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations E. Gillman Dominic C. Rose J. P. Garrahan AI4CE 59 4 0 28 Sep 2022
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths Lars Holdijk Yuanqi Du F. Hooft P. Jaini B. Ensing Max Welling 58 29 0 27 Jun 2022
Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection Thomas Power Dmitry Berenson 86 32 0 10 May 2022
Probabilistic Control and Majorization of Optimal Control Tom Lefebvre 38 2 0 06 May 2022
Global convergence of optimized adaptive importance samplers Ömer Deniz Akyildiz 103 7 0 02 Jan 2022
Nonparametric inference of stochastic differential equations based on the relative entropy rate Min Dai Jinqiao Duan Jianyu Hu Xiangjun Wang 43 2 0 09 Dec 2021
Rare Events via Cross-Entropy Population Monte Carlo Caleb Miller J. Corcoran M. Schneider 43 9 0 12 Oct 2021
On Unbiased Score Estimation for Partially Observed Diffusions J. Heng J. Houssineau Ajay Jasra 70 11 0 11 May 2021
Reinforcement learning of rare diffusive dynamics Avishek Das Dominic C. Rose J. P. Garrahan David T. Limmer 109 28 0 10 May 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 93 78 0 15 Feb 2021
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi 110 3 0 16 Nov 2020
Reinforcement Learning as Iterative and Amortised Inference Beren Millidge Alexander Tschantz A. Seth Christopher L. Buckley OffRL 52 3 0 13 Jun 2020
A reinforcement learning approach to rare trajectory sampling Dominic C. Rose Jamie F. Mair J. P. Garrahan 76 52 0 26 May 2020
Adaptive Smoothing Path Integral Control Dominik Thalmeier H. Kappen Simone Totaro Vicencc Gómez 19 7 0 13 May 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space Nikolas Nusken Lorenz Richter AI4CE 85 112 0 11 May 2020
Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty Jung-Su Ha Danny Driess Marc Toussaint 36 19 0 09 Mar 2020
Schrödinger Bridge Samplers Espen Bernton J. Heng Arnaud Doucet Pierre E. Jacob 70 25 0 31 Dec 2019
Deep Value Model Predictive Control Farbod Farshidian David Hoeller Marco Hutter 58 45 0 08 Oct 2019
Evolutionary reinforcement learning of dynamical large deviations S. Whitelam Daniel A. Jacobson Isaac Tamblyn 51 22 0 02 Sep 2019
Learning to Guide: Guidance Law Based on Deep Meta-learning and Model Predictive Path Integral Control Chen Liang Weihong Wang Zhenghua Liu Chao Lai Benchun Zhou 49 29 0 15 Apr 2019
Convergence rates for optimised adaptive importance samplers Ömer Deniz Akyildiz Joaquín Míguez 133 31 0 28 Mar 2019
Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi BDL 81 27 0 05 Jul 2018
Controlled Sequential Monte Carlo J. Heng A. Bishop George Deligiannidis Arnaud Doucet 108 74 0 28 Aug 2017
Particle Smoothing for Hidden Diffusion Processes: Adaptive Path Integral Smoother H. Ruiz H. Kappen 157 37 0 01 May 2016
Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment Jung-Su Ha Soon-Seo Park Han-Lim Choi 43 7 0 16 Mar 2016
A Topology-Guided Path Integral Approach for Stochastic Optimal Control Jung-Su Ha Han-Lim Choi 45 11 0 19 Oct 2015