Saved in:
| Main Authors: | Aitio, Antti, Jöst, Dominik, Sauer, Dirk Uwe, Howey, David A. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2304.13666 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Li-ion battery health and degradation modes from data with aging-aware circuit models
by: Zhou, Zihao, et al.
Published: (2024)
by: Zhou, Zihao, et al.
Published: (2024)
Fast dynamic time warping and clustering in C++
by: Kumtepeli, Volkan, et al.
Published: (2023)
by: Kumtepeli, Volkan, et al.
Published: (2023)
Byzantine-resilient federated online learning for Gaussian process regression
by: Zhang, Xu, et al.
Published: (2025)
by: Zhang, Xu, et al.
Published: (2025)
Polynomial Chaos Expanded Gaussian Process
by: Polke, Dominik, et al.
Published: (2024)
by: Polke, Dominik, et al.
Published: (2024)
A new approach for combined model class selection and parameters learning for auto-regressive neural models
by: Sgadari, Corrado, et al.
Published: (2026)
by: Sgadari, Corrado, et al.
Published: (2026)
A robust and adaptive MPC formulation for Gaussian process models
by: Dubied, Mathieu, et al.
Published: (2025)
by: Dubied, Mathieu, et al.
Published: (2025)
Dynamic financial processes identification using sparse regressive reservoir computers
by: Vides, Fredy, et al.
Published: (2023)
by: Vides, Fredy, et al.
Published: (2023)
Towards safe control parameter tuning in distributed multi-agent systems
by: Tokmak, Abdullah, et al.
Published: (2025)
by: Tokmak, Abdullah, et al.
Published: (2025)
PyBOP: A Python package for battery model optimisation and parameterisation
by: Planden, Brady, et al.
Published: (2024)
by: Planden, Brady, et al.
Published: (2024)
Gaussian process-based online health monitoring and fault analysis of lithium-ion battery systems from field data
by: Schaeffer, Joachim, et al.
Published: (2024)
by: Schaeffer, Joachim, et al.
Published: (2024)
Current and temperature imbalances in parallel-connected grid storage battery modules
by: Ross, Joseph, et al.
Published: (2026)
by: Ross, Joseph, et al.
Published: (2026)
Lead-acid battery lifetime extension in solar home systems under different operating conditions
by: Perriment, Rebecca, et al.
Published: (2023)
by: Perriment, Rebecca, et al.
Published: (2023)
Building a temperature forecasting model for the city with the regression neural network (RNN)
by: Tran, Nguyen Phuc, et al.
Published: (2024)
by: Tran, Nguyen Phuc, et al.
Published: (2024)
Diagnostic-free onboard battery health assessment
by: Che, Yunhong, et al.
Published: (2025)
by: Che, Yunhong, et al.
Published: (2025)
Safe Bayesian optimization across noise models via scenario programming
by: Tokmak, Abdullah, et al.
Published: (2025)
by: Tokmak, Abdullah, et al.
Published: (2025)
Opportunities for real-time process control of electrode properties in lithium-ion battery manufacturing
by: Hallemans, Noël, et al.
Published: (2025)
by: Hallemans, Noël, et al.
Published: (2025)
Physics-based battery model parametrisation from impedance data
by: Hallemans, Noël, et al.
Published: (2024)
by: Hallemans, Noël, et al.
Published: (2024)
Towards safe Bayesian optimization with Wiener kernel regression
by: Molodchyk, Oleksii, et al.
Published: (2024)
by: Molodchyk, Oleksii, et al.
Published: (2024)
Bayesian dynamic scheduling of multipurpose batch processes under incomplete look-ahead information
by: Zheng, Taicheng, et al.
Published: (2025)
by: Zheng, Taicheng, et al.
Published: (2025)
Efficient identification of linear, parameter-varying, and nonlinear systems with noise models
by: Bemporad, Alberto, et al.
Published: (2025)
by: Bemporad, Alberto, et al.
Published: (2025)
Magnetic field estimation using Gaussian process regression for interactive wireless power system design
by: Honjo, Yuichi, et al.
Published: (2025)
by: Honjo, Yuichi, et al.
Published: (2025)
Trustworthy and Explainable Deep Reinforcement Learning for Safe and Energy-Efficient Process Control: A Use Case in Industrial Compressed Air Systems
by: Bezold, Vincent, et al.
Published: (2025)
by: Bezold, Vincent, et al.
Published: (2025)
Gradient Networks for Universal Magnetic Modeling of Synchronous Machines
by: Li, Junyi, et al.
Published: (2026)
by: Li, Junyi, et al.
Published: (2026)
Driving behavior-guided battery health monitoring for electric vehicles using machine learning
by: Jiang, Nanhua, et al.
Published: (2023)
by: Jiang, Nanhua, et al.
Published: (2023)
Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics
by: Hansen, Martine Dyring, et al.
Published: (2025)
by: Hansen, Martine Dyring, et al.
Published: (2025)
Local Bayesian Optimization for Controller Tuning with Crash Constraints
by: von Rohr, Alexander, et al.
Published: (2024)
by: von Rohr, Alexander, et al.
Published: (2024)
Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries
by: Lanubile, Andrea, et al.
Published: (2024)
by: Lanubile, Andrea, et al.
Published: (2024)
Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
by: Sheng, Xinyi, et al.
Published: (2025)
by: Sheng, Xinyi, et al.
Published: (2025)
Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part I
by: Tian, Yi, et al.
Published: (2022)
by: Tian, Yi, et al.
Published: (2022)
Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part II
by: Tian, Yi, et al.
Published: (2026)
by: Tian, Yi, et al.
Published: (2026)
Pseudo-random sequences for low-cost operando impedance measurements of Li-ion batteries
by: Sihvo, Jussi, et al.
Published: (2025)
by: Sihvo, Jussi, et al.
Published: (2025)
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
by: Zaspel, Peter, et al.
Published: (2024)
by: Zaspel, Peter, et al.
Published: (2024)
State space models, emergence, and ergodicity: How many parameters are needed for stable predictions?
by: Ziemann, Ingvar, et al.
Published: (2024)
by: Ziemann, Ingvar, et al.
Published: (2024)
Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
by: Hsin, Junette, et al.
Published: (2023)
by: Hsin, Junette, et al.
Published: (2023)
Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
by: Ewering, Jan-Hendrik, et al.
Published: (2025)
by: Ewering, Jan-Hendrik, et al.
Published: (2025)
PACSBO: Probably approximately correct safe Bayesian optimization
by: Tokmak, Abdullah, et al.
Published: (2024)
by: Tokmak, Abdullah, et al.
Published: (2024)
Integrating Lagrangian Neural Networks into the Dyna Framework for Reinforcement Learning
by: Das, Shreya, et al.
Published: (2026)
by: Das, Shreya, et al.
Published: (2026)
Learning Passive Continuous-Time Dynamics with Multistep Port-Hamiltonian Gaussian Processes
by: Leung, Chi Ho, et al.
Published: (2025)
by: Leung, Chi Ho, et al.
Published: (2025)
Streaming Generated Gaussian Process Experts for Online Learning and Control: Extended Version
by: Yang, Zewen, et al.
Published: (2025)
by: Yang, Zewen, et al.
Published: (2025)
BUILDA: A Thermal Building Data Generation Framework for Transfer Learning
by: Krug, Thomas, et al.
Published: (2025)
by: Krug, Thomas, et al.
Published: (2025)
Similar Items
-
Learning Li-ion battery health and degradation modes from data with aging-aware circuit models
by: Zhou, Zihao, et al.
Published: (2024) -
Fast dynamic time warping and clustering in C++
by: Kumtepeli, Volkan, et al.
Published: (2023) -
Byzantine-resilient federated online learning for Gaussian process regression
by: Zhang, Xu, et al.
Published: (2025) -
Polynomial Chaos Expanded Gaussian Process
by: Polke, Dominik, et al.
Published: (2024) -
A new approach for combined model class selection and parameters learning for auto-regressive neural models
by: Sgadari, Corrado, et al.
Published: (2026)