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2402.06276
Cited By
Safe Active Learning for Time-Series Modeling with Gaussian Processes
9 February 2024
Christoph Zimmer
Mona Meister
D. Nguyen-Tuong
AI4TS
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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
151
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
34
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
16
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
26
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
23
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
15
0
0
29 Nov 2021
Active Learning of Driving Scenario Trajectories
Sanna Jarl
Linus Aronsson
Sadegh Rahrovani
M. Chehreghani
12
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
6
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
16
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
13
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
9
8
0
22 May 2020
Actively Learning Gaussian Process Dynamics
Mona Buisson-Fenet
Friedrich Solowjow
Sebastian Trimpe
GP
14
64
0
22 Nov 2019
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves
Stefan Meintrup
Alexander Munteanu
Dennis Rohde
14
10
0
16 Jul 2019
Safe Exploration in Markov Decision Processes
T. Moldovan
Pieter Abbeel
78
308
0
22 May 2012
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