Gaussian Processes for Data-Efficient Learning in Robotics and Control

10 February 2015

Papers citing "Gaussian Processes for Data-Efficient Learning in Robotics and Control"

50 / 235 papers shown

Title
Data-efficient Model Learning and Prediction for Contact-rich Manipulation Tasks S. A. Khader Hang Yin Pietro Falco Danica Kragic 6 2 0 11 Sep 2019
High Dimensional Bayesian Optimization via Supervised Dimension Reduction Miao Zhang Huiqi Li Steven W. Su 27 44 0 21 Jul 2019
Adaptive Prior Selection for Repertoire-based Online Adaptation in Robotics Rituraj Kaushik P. Desreumaux Jean-Baptiste Mouret OffRL 27 34 0 16 Jul 2019
The Use of Gaussian Processes in System Identification Simo Särkkä GP AI4TS 22 8 0 13 Jul 2019
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms Oliver Kroemer S. Niekum George Konidaris 41 356 0 06 Jul 2019
Benchmarking Model-Based Reinforcement Learning Tingwu Wang Xuchan Bao I. Clavera Jerrick Hoang Yeming Wen Eric D. Langlois Matthew Shunshi Zhang Guodong Zhang Pieter Abbeel Jimmy Ba OffRL 34 359 0 03 Jul 2019
Dynamics-Aware Unsupervised Discovery of Skills Archit Sharma S. Gu Sergey Levine Vikash Kumar Karol Hausman 42 399 0 02 Jul 2019
Active Learning of Dynamics for Data-Driven Control Using Koopman Operators Ian Abraham Todd D. Murphey 24 160 0 12 Jun 2019
A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives Alexander Fabisch Christoph Petzoldt M. Otto Frank Kirchner AI4CE 17 13 0 05 Jun 2019
Proximal Reliability Optimization for Reinforcement Learning Narendra Patwardhan Zequn Wang 18 0 0 03 Jun 2019
Bayesian Evidential Deep Learning with PAC Regularization Manuel Haussmann S. Gerwinn M. Kandemir UQCV EDL BDL 14 1 0 03 Jun 2019
Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction Narendra Patwardhan Zequn Wang 22 1 0 15 May 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 19 28 0 15 Apr 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features Arno Solin Manon Kok 18 23 0 10 Apr 2019
Exact Gaussian Processes on a Million Data Points Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger A. Wilson GP 24 226 0 19 Mar 2019
Financial Applications of Gaussian Processes and Bayesian Optimization Joan Gonzalvez Edmond Lezmi T. Roncalli Jiali Xu 20 54 0 12 Mar 2019
Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device A. Kalinowska Thomas A. Berrueta A. Zoss Todd D. Murphey 18 9 0 28 Feb 2019
Total stochastic gradient algorithms and applications in reinforcement learning Paavo Parmas 36 17 0 05 Feb 2019
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos Paavo Parmas C. Rasmussen Jan Peters Kenji Doya 13 85 0 04 Feb 2019
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning Nathan Lambert Daniel S. Drew Joseph Yaconelli Roberto Calandra Sergey Levine K. Pister 11 145 0 11 Jan 2019
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System Xinshi Chen Shuang Li Hui Li Shaohua Jiang Yuan Qi Le Song 22 207 0 27 Dec 2018
GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language Jamie Fairbrother Christopher Nemeth M. Rischard Johanni Brea Thomas Pinder GP VLM 32 24 0 21 Dec 2018
Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study Matthias Neumann-Brosig A. Marco D. Schwarzmann Sebastian Trimpe 24 91 0 15 Dec 2018
Residual Policy Learning Tom Silver Kelsey R. Allen J. Tenenbaum L. Kaelbling OffRL 26 173 0 15 Dec 2018
An Algorithmic Perspective on Imitation Learning Takayuki Osa Joni Pajarinen Gerhard Neumann J. Andrew Bagnell Pieter Abbeel Jan Peters 50 830 0 16 Nov 2018
A Hybrid Approach for Trajectory Control Design L. Freda M. Gianni F. Pirri 14 0 0 08 Oct 2018
Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills Hejia Zhang Eric Heiden Stefanos Nikolaidis Joseph J. Lim Gaurav Sukhatme 12 10 0 29 Sep 2018
Combining Simulations and Real-robot Experiments for Bayesian Optimization of Bipedal Gait Stabilization Diego Rodriguez André Brandenburger Sven Behnke 6 14 0 14 Sep 2018
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze Diego Romeres Devesh K. Jha Alberto Dalla Libera W. Yerazunis D. Nikovski 35 28 0 13 Sep 2018
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning Marvin Zhang Sharad Vikram Laura M. Smith Pieter Abbeel Matthew J. Johnson Sergey Levine OffRL 23 41 0 28 Aug 2018
A survey on policy search algorithms for learning robot controllers in a handful of trials Konstantinos Chatzilygeroudis Vassilis Vassiliades F. Stulp Sylvain Calinon Jean-Baptiste Mouret 17 155 0 06 Jul 2018
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards Rituraj Kaushik Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 31 19 0 25 Jun 2018
Stable Gaussian Process based Tracking Control of Euler-Lagrange Systems Thomas Beckers Dana Kulić Sandra Hirche 11 123 0 19 Jun 2018
Combining Model-Free Q-Ensembles and Model-Based Approaches for Informed Exploration Sreecharan Sankaranarayanan Raghuram Mandyam Annasamy Katia Sycara Carolyn Rose 17 0 0 12 Jun 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Kurtland Chua Roberto Calandra R. McAllister Sergey Levine BDL 30 1,254 0 30 May 2018
Data-driven Policy Transfer with Imprecise Perception Simulation M. Pecka Karel Zimmermann Matěj Petrlík Tomáš Svoboda 22 11 0 05 Apr 2018
Meta Reinforcement Learning with Latent Variable Gaussian Processes Steindór Sæmundsson Katja Hofmann M. Deisenroth BDL OffRL AI4CE 34 142 0 20 Mar 2018
Learning non-Gaussian Time Series using the Box-Cox Gaussian Process Gonzalo Rios Felipe A. Tobar GP 21 14 0 19 Mar 2018
Constant-Time Predictive Distributions for Gaussian Processes Geoff Pleiss Jacob R. Gardner Kilian Q. Weinberger A. Wilson 25 94 0 16 Mar 2018
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning J. A. G. Higuera David Meger Gregory Dudek BDL 22 39 0 06 Mar 2018
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making L. Zintgraf D. Roijers Sjoerd Linders Catholijn M. Jonker A. Nowé 16 49 0 21 Feb 2018
Composite Gaussian Processes: Scalable Computation and Performance Analysis Xiuming Liu Dave Zachariah Edith C.H. Ngai 16 0 0 31 Jan 2018
Kernel Distillation for Fast Gaussian Processes Prediction Congzheng Song Yiming Sun GP 13 1 0 31 Jan 2018
Algorithmic Linearly Constrained Gaussian Processes Markus Lange-Hegermann 26 34 0 28 Jan 2018
Diff-DAC: Distributed Actor-Critic for Average Multitask Deep Reinforcement Learning Sergio Valcarcel Macua Aleksi Tukiainen D. Hernández David Baldazo Enrique Munoz de Cote S. Zazo 32 29 0 28 Oct 2017
Safe Learning of Quadrotor Dynamics Using Barrier Certificates Li Wang Evangelos A. Theodorou M. Egerstedt 11 190 0 16 Oct 2017
Learning Unmanned Aerial Vehicle Control for Autonomous Target Following Siyi Li Tianbo Liu Chi Zhang Dit-Yan Yeung Shaojie Shen 6 37 0 24 Sep 2017
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search Rémi Pautrat Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 34 44 0 20 Sep 2017
Using Parameterized Black-Box Priors to Scale Up Model-Based Policy Search for Robotics Konstantinos Chatzilygeroudis Jean-Baptiste Mouret 23 45 0 20 Sep 2017
MBMF: Model-Based Priors for Model-Free Reinforcement Learning Somil Bansal Roberto Calandra Kurtland Chua Sergey Levine Claire Tomlin OffRL 27 36 0 10 Sep 2017