Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control

4 June 2019

Papers citing "Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control"

23 / 23 papers shown

Title
Convergence Rates of Constrained Expected Improvement Haowei Wang Jingyi Wang Zhongxiang Dai Nai-Yuan Chiang Szu Hui Ng Cosmin G. Petra 27 0 0 16 May 2025
Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics Manish Prajapat Johannes Köhler Amon Lahr Andreas Krause Melanie Zeilinger 40 0 0 12 May 2025
Towards safe Bayesian optimization with Wiener kernel regression O. Molodchyk Johannes Teutsch T. Faulwasser 31 0 0 04 Nov 2024
Towards Safe Multi-Task Bayesian Optimization Jannis O. Lübsen Christian Hespe Annika Eichler 29 3 0 12 Dec 2023
Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems Jason J. Choi F. Castañeda Wonsuhk Jung Bike Zhang Claire J. Tomlin Koushil Sreenath 42 3 0 23 Nov 2023
Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy Zhenxiao Yin X. Dai Zewen Yang Yang-Wu Shen Georges Hattab Haiying Zhao 33 10 0 26 Jul 2023
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning X. Dai Armin Lederer Zewen Yang Sandra Hirche 46 13 0 14 May 2023
Safe Machine-Learning-supported Model Predictive Force and Motion Control in Robotics Janine Matschek Johanna Bethge R. Findeisen 45 8 0 08 Mar 2023
Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions Armin Lederer Azra Begzadić Neha Das Sandra Hirche 26 4 0 01 Dec 2022
Safe and Efficient Reinforcement Learning Using Disturbance-Observer-Based Control Barrier Functions Yikun Cheng Pan Zhao N. Hovakimyan OffRL 30 11 0 30 Nov 2022
Safe and Efficient Exploration of Human Models During Human-Robot Interaction Ravi Pandya Changliu Liu 24 6 0 01 Aug 2022
Barrier Certified Safety Learning Control: When Sum-of-Square Programming Meets Reinforcement Learning He-lu Huang Zerui Li Dongkun Han 42 2 0 16 Jun 2022
Scaling ResNets in the Large-depth Regime Pierre Marion Adeline Fermanian Gérard Biau Jean-Philippe Vert 31 16 0 14 Jun 2022
Networked Online Learning for Control of Safety-Critical Resource-Constrained Systems based on Gaussian Processes Armin Lederer Mingmin Zhang Samuel Tesfazgi Sandra Hirche 24 3 0 23 Feb 2022
Adaptive Low-Pass Filtering using Sliding Window Gaussian Processes Alejandro Jose Ordóñez Conejo Armin Lederer Sandra Hirche 28 4 0 05 Nov 2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications A. Capone Armin Lederer Sandra Hirche 32 18 0 06 Sep 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression Christian Fiedler C. Scherer Sebastian Trimpe GP 31 65 0 06 May 2021
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach A. Hakobyan Insoon Yang 112 25 0 03 May 2021
Deterministic error bounds for kernel-based learning techniques under bounded noise E. Maddalena Paul Scharnhorst Colin N. Jones 33 45 0 10 Aug 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 38 82 0 15 Jun 2020
GP3: A Sampling-based Analysis Framework for Gaussian Processes Armin Lederer M. Kessler Sandra Hirche GP 24 2 0 14 Jun 2020
How Training Data Impacts Performance in Learning-based Control Armin Lederer A. Capone Jonas Umlauft Sandra Hirche 33 17 0 25 May 2020
Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties Richard Cheng M. J. Khojasteh Aaron D. Ames J. W. Burdick 27 87 0 11 Apr 2020