Safe Active Learning for Time-Series Modeling with Gaussian Processes

9 February 2024

Papers citing "Safe Active Learning for Time-Series Modeling with Gaussian Processes"

32 / 32 papers shown

Title
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies from Simulated Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer OffRL 153 0 0 26 Jan 2025
First, Learn What You Don't Know: Active Information Gathering for Driving at the Limits of Handling Alexander Davydov Franck Djeumou Marcus Greiff Makoto Suminaka Michael Thompson John Subosits Thomas Lew 53 0 0 31 Oct 2024
Reciprocal Learning Julian Rodemann Christoph Jansen G. Schollmeyer FedML 37 0 0 12 Aug 2024
Batch Active Learning in Gaussian Process Regression using Derivatives Hon Sum Alec Yu Christoph Zimmer D. Nguyen-Tuong GP 26 1 0 03 Aug 2024
Amortized Active Learning for Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer 18 0 0 25 Jul 2024
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes Markus Lange-Hegermann Christoph Zimmer AI4TS 47 0 0 17 May 2024
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning Jörn Tebbe Christoph Zimmer A. Steland Markus Lange-Hegermann Fabian Mies GP 18 3 0 28 Feb 2024
Global Safe Sequential Learning via Efficient Knowledge Transfer Cen-You Li Olaf Duennbier Marc Toussaint Barbara Rakitsch Christoph Zimmer 52 2 0 22 Feb 2024
Combining Thermodynamics-based Model of the Centrifugal Compressors and Active Machine Learning for Enhanced Industrial Design Optimization Shadi Ghiasi Guido Pazzi Concettina Del Grosso Giovanni De Magistris Giacomo Veneri AI4CE 16 1 0 06 Sep 2023
Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels M. Bitzer Mona Meister Christoph Zimmer 14 9 0 16 Jun 2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning D. Wu Ruijia Niu Matteo Chinazzi Yi Ma Rose Yu AI4CE 30 7 0 07 May 2023
Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems Ce Zhang Kailiang Wu Zhihai He 27 0 0 15 Apr 2023
Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems M. Bitzer Mona Meister Christoph Zimmer 16 4 0 17 Mar 2023
Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients Marc Härkönen Markus Lange-Hegermann Bogdan Raiță 29 15 0 29 Dec 2022
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport M. Bitzer Mona Meister Christoph Zimmer 4 9 0 21 Oct 2022
On boundary conditions parametrized by analytic functions Markus Lange-Hegermann D. Robertz 18 5 0 06 May 2022
Safe Active Learning for Multi-Output Gaussian Processes Cen-You Li Barbara Rakitsch Christoph Zimmer UQCV 14 17 0 28 Mar 2022
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation Aivar Sootla Alexander I. Cowen-Rivers Taher Jafferjee Ziyan Wang D. Mguni Jun Wang Haitham Bou-Ammar 29 54 0 14 Feb 2022
Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey M. Askarpour Alan Wassyng M. Lawford R. Paige Z. Diskin 17 0 0 29 Nov 2021
Active Learning of Driving Scenario Trajectories Sanna Jarl Linus Aronsson Sadegh Rahrovani M. Chehreghani 14 18 0 06 Aug 2021
Active Learning in Gaussian Process State Space Model H. Yu Dingling Yao Christoph Zimmer Marc Toussaint D. Nguyen-Tuong GP 8 4 0 30 Jul 2021
Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach B. Varga Balázs Kulcsár M. Chehreghani 18 1 0 19 Jul 2021
Deep Bayesian Active Learning for Accelerating Stochastic Simulation D. Wu Ruijia Niu Matteo Chinazzi Alessandro Vespignani Yi Ma Rose Yu AI4CE 30 8 0 05 Jun 2021
Convolutional Normalizing Flows for Deep Gaussian Processes Haibin Yu Dapeng Liu Yizhou Chen K. H. Low P. Jaillet BDL 15 6 0 17 Apr 2021
A Taylor Based Sampling Scheme for Machine Learning in Computational Physics Paul Novello Gaël Poëtte D. Lugato P. Congedo PINN AI4CE 21 0 0 20 Jan 2021
Active Model Learning using Informative Trajectories for Improved Closed-Loop Control on Real Robots Weixuan Zhang M. Tognon Lionel Ott Roland Siegwart Juan I. Nieto 14 7 0 20 Jan 2021
Meta-active Learning in Probabilistically-Safe Optimization Mariah L. Schrum M. Connolly Eric R. Cole Mihir Ghetiya R. Gross Matthew C. Gombolay 15 12 0 07 Jul 2020
SAMBA: Safe Model-Based & Active Reinforcement Learning Alexander I. Cowen-Rivers Daniel Palenicek Vincent Moens Mohammed Abdullah Aivar Sootla Jun Wang Haitham Bou-Ammar 21 44 0 12 Jun 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties J. Lindinger David Reeb C. Lippert Barbara Rakitsch BDL UQCV 11 8 0 22 May 2020
Actively Learning Gaussian Process Dynamics Mona Buisson-Fenet Friedrich Solowjow Sebastian Trimpe GP 16 64 0 22 Nov 2019
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves Stefan Meintrup Alexander Munteanu Dennis Rohde 16 10 0 16 Jul 2019
Safe Exploration in Markov Decision Processes T. Moldovan Pieter Abbeel 78 308 0 22 May 2012