The Differentiable Cross-Entropy Method

27 September 2019

Papers citing "The Differentiable Cross-Entropy Method"

41 / 41 papers shown

Title
Skill-based Safe Reinforcement Learning with Risk Planning Hanping Zhang Yuhong Guo OffRL OnRL 40 0 0 02 May 2025
Preference-Optimized Pareto Set Learning for Blackbox Optimization Zhang Haishan Diptesh Das Koji Tsuda 41 1 0 19 Aug 2024
Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach Anton Plaksin Vitaly Kalev 21 0 0 03 May 2024
A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning Ran Wei Nathan Lambert Anthony D. McDonald Alfredo Garcia Roberto Calandra 33 6 0 10 Oct 2023
Deep Model Predictive Optimization Jacob Sacks Rwik Rana Kevin Huang Alex Spitzer Guanya Shi Byron Boots 43 7 0 06 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 37 16 0 22 Sep 2023
Learning Covariances for Estimation with Constrained Bilevel Optimization Mohamad Qadri Zachary Manchester Michael Kaess 29 4 0 18 Sep 2023
Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation Mohamad Qadri Michael Kaess 32 4 0 05 Sep 2023
Graph Reinforcement Learning for Network Control via Bi-Level Optimization Daniele Gammelli James Harrison Kaidi Yang Marco Pavone Filipe Rodrigues Francisco Câmara Pereira AI4CE 33 6 0 16 May 2023
A Simple Decentralized Cross-Entropy Method Zichen Zhang Jun Jin Martin Jägersand Jun Luo Dale Schuurmans 13 8 0 16 Dec 2022
PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization Qiqi Duan Guochen Zhou Chang Shao Zhuowei Wang Mingyang Feng Yuwei Huang Yajing Tan Yijun Yang Qi Zhao Yuhui Shi 26 5 0 12 Dec 2022
Learning to Optimize in Model Predictive Control Jacob Sacks Byron Boots 21 22 0 05 Dec 2022
Learning Sampling Distributions for Model Predictive Control Jacob Sacks Byron Boots 11 21 0 05 Dec 2022
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation Linfeng Zhao Huazhe Xu Lawson L. S. Wong 37 6 0 24 Oct 2022
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems Aaron Ferber Taoan Huang Daochen Zha M. Schubert Benoit Steiner B. Dilkina Yuandong Tian 41 20 0 22 Oct 2022
Integrating Symmetry into Differentiable Planning with Steerable Convolutions Linfeng Zhao Xu Zhu Lingzhi Kong Robin G. Walters Lawson L. S. Wong 20 7 0 08 Jun 2022
Regret-Aware Black-Box Optimization with Natural Gradients, Trust-Regions and Entropy Control Maximilian Hüttenrauch Gerhard Neumann 13 1 0 24 May 2022
Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM M. Pereira A. Saravanos Oswin So Evangelos A. Theodorou 22 15 0 22 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Scalable Online Planning via Reinforcement Learning Fine-Tuning Arnaud Fickinger Hengyuan Hu Brandon Amos Stuart J. Russell Noam Brown 49 21 0 30 Sep 2021
Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration Haobo Jiang Yaqi Shen Jin Xie Jun Li J. Qian Jian Yang 3DPC 51 39 0 14 Sep 2021
Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration Haobo Jiang Jin Xie J. Qian Jian Yang 3DPC 21 10 0 05 Aug 2021
LEO: Learning Energy-based Models in Factor Graph Optimization Paloma Sodhi Eric Dexheimer Mustafa Mukadam Stuart Anderson Michael Kaess 40 16 0 04 Aug 2021
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation Evgenii Nikishin Romina Abachi Rishabh Agarwal Pierre-Luc Bacon OffRL 52 34 0 06 Jun 2021
A Reinforcement Learning based Path Planning Approach in 3D Environment Geesara Kulathunga 14 24 0 21 May 2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints Anselm Paulus Michal Rolínek Vít Musil Brandon Amos Georg Martius 20 60 0 05 May 2021
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning Luis Pineda Brandon Amos Amy Zhang Nathan Lambert Roberto Calandra OffRL 20 46 0 20 Apr 2021
Neuro-algorithmic Policies enable Fast Combinatorial Generalization Marin Vlastelica Michal Rolínek Georg Martius 25 17 0 15 Feb 2021
Latent Skill Planning for Exploration and Transfer Kevin Xie Homanga Bharadhwaj Danijar Hafner Animesh Garg Florian Shkurti 39 20 0 27 Nov 2020
Iterative Amortized Policy Optimization Joseph Marino Alexandre Piché Alessandro Davide Ialongo Yisong Yue OffRL 63 21 0 20 Oct 2020
Differentiable Implicit Layers Andreas Look Simona Doneva M. Kandemir Rainer Gemulla Jan Peters 24 9 0 14 Oct 2020
Sample-efficient Cross-Entropy Method for Real-time Planning Cristina Pinneri Shambhuraj Sawant Sebastian Blaes Jan Achterhold Joerg Stueckler Michal Rolínek Georg Martius 24 98 0 14 Aug 2020
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control Ioannis Exarchos M. Pereira Ziyi Wang Evangelos A. Theodorou 13 4 0 22 Jun 2020
Learning Convex Optimization Models Akshay Agrawal Shane T. Barratt Stephen P. Boyd 19 40 0 07 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 30 118 0 07 Jun 2020
Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization Homanga Bharadhwaj Kevin Xie Florian Shkurti 13 49 0 19 Apr 2020
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 19 23 0 10 Apr 2019
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 39 65 0 08 Oct 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 187 599 0 22 Sep 2016
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 89 271 0 24 Feb 2014