Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression

6 May 2021

Papers citing "Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression"

34 / 34 papers shown

Title
The Hardness of Validating Observational Studies with Experimental Data Jake Fawkes Michael O'Riordan Athanasios Vlontzos Oriol Corcoll Ciarán M. Gilligan-Lee 53 1 0 19 Mar 2025
Safe exploration in reproducing kernel Hilbert spaces Abdullah Tokmak Kiran G. Krishnan Thomas B. Schon Dominik Baumann 32 0 0 13 Mar 2025
Vector Optimization with Gaussian Process Bandits İlter Onat Korkmaz Yaşar Cahit Yıldırım Çağın Ararat Cem Tekin 66 0 0 03 Dec 2024
Towards safe Bayesian optimization with Wiener kernel regression O. Molodchyk Johannes Teutsch T. Faulwasser 21 0 0 04 Nov 2024
Conformal Prediction for Dose-Response Models with Continuous Treatments Jarne Verhaeghe Jef Jonkers Sofie Van Hoecke 23 0 0 30 Sep 2024
Safe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control Sebastian Hirt Maik Pfefferkorn R. Findeisen 11 3 0 16 Sep 2024
PACSBO: Probably approximately correct safe Bayesian optimization Abdullah Tokmak Thomas B. Schon Dominik Baumann 24 2 0 02 Sep 2024
Data-Driven Abstractions via Binary-Tree Gaussian Processes for Formal Verification Oliver Schon Shammakh Naseer B. Wooding Sadegh Soudjani 25 1 0 15 Jul 2024
Meta-Analysis with Untrusted Data Shiva Kaul Geoffrey J. Gordon CML 32 1 0 12 Jul 2024
Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling Shifan Zhao Jiaying Lu Carl Yang Edmond Chow Yuanzhe Xi 34 1 0 22 May 2024
On Safety in Safe Bayesian Optimization Christian Fiedler Johanna Menn Lukas Kreisköther Sebastian Trimpe 26 9 0 19 Mar 2024
Information-Theoretic Safe Bayesian Optimization A. Bottero Carlos E. Luis Julia Vinogradska Felix Berkenkamp Jan Peters 27 1 0 23 Feb 2024
Bayesian optimization as a flexible and efficient design framework for sustainable process systems J. Paulson Calvin Tsay TPM 32 12 0 29 Jan 2024
Safe reinforcement learning in uncertain contexts Dominik Baumann Thomas B. Schon OffRL 11 0 0 11 Jan 2024
Automatic nonlinear MPC approximation with closed-loop guarantees Abdullah Tokmak Christian Fiedler M. Zeilinger Sebastian Trimpe Johannes Köhler 11 4 0 15 Dec 2023
Towards Safe Multi-Task Bayesian Optimization Jannis O. Lübsen Christian Hespe Annika Eichler 11 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 K. Sreenath 25 3 0 23 Nov 2023
Lipschitz and Hölder Continuity in Reproducing Kernel Hilbert Spaces Christian Fiedler 17 1 0 27 Oct 2023
Guaranteed Coverage Prediction Intervals with Gaussian Process Regression Harris Papadopoulos 24 10 0 24 Oct 2023
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis 41 1 0 16 Oct 2023
Exact Inference for Continuous-Time Gaussian Process Dynamics K. Ensinger Nicholas Tagliapietra Sebastian Ziesche Sebastian Trimpe 11 1 0 05 Sep 2023
Robust Bayesian Satisficing Artun Saday Yacsar Cahit Yildirim Cem Tekin 75 2 0 16 Aug 2023
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty Futoshi Futami Tomoharu Iwata UD PER 15 3 0 23 Jul 2023
Episodic Gaussian Process-Based Learning Control with Vanishing Tracking Errors Armin Lederer Jonas Umlauft Sandra Hirche 24 0 0 10 Jul 2023
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization Daniel Widmer Dong-oh Kang Bhavya Sukhija Jonas Hubotter Andreas Krause Stelian Coros 21 14 0 12 Jun 2023
Error Bounds for Kernel-Based Linear System Identification with Unknown Hyperparameters Mingzhou Yin Roy S. Smith 12 0 0 17 Mar 2023
BO-Muse: A human expert and AI teaming framework for accelerated experimental design Sunil R. Gupta A. Shilton V. ArunKumarA. S. Ryan Majid Abdolshah Hung Le Santu Rana Julian Berk Mahad Rashid Svetha Venkatesh 21 7 0 03 Mar 2023
Information-Theoretic Safe Exploration with Gaussian Processes A. Bottero Carlos E. Luis Julia Vinogradska Felix Berkenkamp Jan Peters 13 13 0 09 Dec 2022
Excess risk analysis for epistemic uncertainty with application to variational inference Futoshi Futami Tomoharu Iwata N. Ueda Issei Sato Masashi Sugiyama UQCV 15 1 0 02 Jun 2022
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems Bhavya Sukhija M. Turchetta David Lindner Andreas Krause Sebastian Trimpe Dominik Baumann 18 17 0 24 Jan 2022
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment Eli Ben-Michael D. J. Greiner Kosuke Imai Zhichao Jiang OffRL 23 22 0 22 Sep 2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications A. Capone Armin Lederer Sandra Hirche 6 18 0 06 Sep 2021
Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees Christian Fiedler C. Scherer Sebastian Trimpe 17 15 0 07 May 2021
Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework T. Lew Apoorva Sharma James Harrison Andrew Bylard Marco Pavone 15 44 0 26 Aug 2020