Transfer Learning for Neural Parameter Estimation applied to Building RC Models
Fuente:
arXiv
Saved in:
| Main Authors: | Raisch, Fabian, Germann, Timo, Kutz, J. Nathan, Goebel, Christoph, Tischler, Benjamin |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GenTL: A General Transfer Learning Model for Building Thermal Dynamics
by: Raisch, Fabian, et al.
Published: (2025)
by: Raisch, Fabian, et al.
Published: (2025)
Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts
by: Raisch, Fabian, et al.
Published: (2025)
by: Raisch, Fabian, et al.
Published: (2025)
Thermal-GEMs: Generalized Models for Building Thermal Dynamics
by: Koch, Felix, et al.
Published: (2026)
by: Koch, Felix, et al.
Published: (2026)
BUILDA: A Thermal Building Data Generation Framework for Transfer Learning
by: Krug, Thomas, et al.
Published: (2025)
by: Krug, Thomas, et al.
Published: (2025)
BuilDyn: Excitation-Driven Data Generation for Building Thermal Dynamics Modeling and Control
by: Koch, Felix, et al.
Published: (2026)
by: Koch, Felix, et al.
Published: (2026)
Counter-Dyna: Data-Efficient RL-Based HVAC Control using Counterfactual Building Models
by: de Vargas, Jan Marco Ruiz, et al.
Published: (2026)
by: de Vargas, Jan Marco Ruiz, et al.
Published: (2026)
A Highly Configurable Framework for Large-Scale Thermal Building Data Generation to drive Machine Learning Research
by: Krug, Thomas, et al.
Published: (2025)
by: Krug, Thomas, et al.
Published: (2025)
SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
by: Zolman, Nicholas, et al.
Published: (2024)
by: Zolman, Nicholas, et al.
Published: (2024)
BOOST-RPF: Boosted Sequential Trees for Radial Power Flow
by: Okoyomon, Ehimare, et al.
Published: (2026)
by: Okoyomon, Ehimare, et al.
Published: (2026)
Reservoir computing for system identification and predictive control with limited data
by: Williams, Jan P., et al.
Published: (2024)
by: Williams, Jan P., et al.
Published: (2024)
Physics-Informed Inductive Biases for Voltage Prediction in Distribution Grids
by: Okoyomon, Ehimare, et al.
Published: (2025)
by: Okoyomon, Ehimare, et al.
Published: (2025)
State-Space Models for Tabular Prior-Data Fitted Networks
by: Koch, Felix, et al.
Published: (2025)
by: Koch, Felix, et al.
Published: (2025)
Transfer Learning for Control Systems via Neural Simulation Relations
by: Nadali, Alireza, et al.
Published: (2024)
by: Nadali, Alireza, et al.
Published: (2024)
Transferable Parasitic Estimation via Graph Contrastive Learning and Label Rebalancing in AMS Circuits
by: Shen, Shan, et al.
Published: (2025)
by: Shen, Shan, et al.
Published: (2025)
Robust and Interpretable Graph Neural Networks for Power Systems State Estimation
by: Yaniv, Arbel, et al.
Published: (2026)
by: Yaniv, Arbel, et al.
Published: (2026)
Learning Transferable Friction Models and LuGre Identification Via Physics-Informed Neural Networks
by: Ozmen, Asutay, et al.
Published: (2025)
by: Ozmen, Asutay, et al.
Published: (2025)
A Digital Twin for Diesel Engines: Operator-infused Physics-Informed Neural Networks with Transfer Learning for Engine Health Monitoring
by: Nath, Kamaljyoti, et al.
Published: (2024)
by: Nath, Kamaljyoti, et al.
Published: (2024)
Learning Stable and Robust Linear Parameter-Varying State-Space Models
by: Verhoek, Chris, et al.
Published: (2023)
by: Verhoek, Chris, et al.
Published: (2023)
Neural Approximators for Low-Thrust Trajectory Transfer Cost and Reachability
by: Zhang, Zhong, et al.
Published: (2025)
by: Zhang, Zhong, et al.
Published: (2025)
Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
by: Hose, Henrik, et al.
Published: (2024)
by: Hose, Henrik, et al.
Published: (2024)
On Building Myopic MPC Policies using Supervised Learning
by: Orrico, Christopher A., et al.
Published: (2024)
by: Orrico, Christopher A., et al.
Published: (2024)
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging
by: Hirt, Sebastian, et al.
Published: (2024)
by: Hirt, Sebastian, et al.
Published: (2024)
Equivalent and Compact Representations of Neural Network Controllers With Decision Trees
by: Chang, Kevin, et al.
Published: (2023)
by: Chang, Kevin, et al.
Published: (2023)
The Silence that Speaks: Neural Estimation via Communication Gaps
by: Aggarwal, Shubham, et al.
Published: (2025)
by: Aggarwal, Shubham, et al.
Published: (2025)
A Quantum Neural Network Transfer-Learning Model for Forecasting Problems with Continuous and Discrete Variables
by: Abdulrahman, Ismael
Published: (2025)
by: Abdulrahman, Ismael
Published: (2025)
A Hierarchical Surrogate Model for Efficient Multi-Task Parameter Learning in Closed-Loop Control
by: Hirt, Sebastian, et al.
Published: (2025)
by: Hirt, Sebastian, et al.
Published: (2025)
Optimal Bayesian Affine Estimator and Active Learning for the Wiener Model
by: Vakili, Sasan, et al.
Published: (2025)
by: Vakili, Sasan, et al.
Published: (2025)
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks
by: Neary, Cyrus, et al.
Published: (2024)
by: Neary, Cyrus, et al.
Published: (2024)
Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
by: Bøhn, Eivind, et al.
Published: (2021)
by: Bøhn, Eivind, et al.
Published: (2021)
Quantifying and Predicting Residential Building Flexibility Using Machine Learning Methods
by: Salter, Patrick, et al.
Published: (2024)
by: Salter, Patrick, et al.
Published: (2024)
Transfer Learning of Multiobjective Indirect Low-Thrust Trajectories Using Diffusion Models and Markov Chain Monte Carlo
by: Graebner, Jannik, et al.
Published: (2026)
by: Graebner, Jannik, et al.
Published: (2026)
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks
by: Kneifl, Jonas, et al.
Published: (2024)
by: Kneifl, Jonas, et al.
Published: (2024)
BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning
by: Liu, Ruohong, et al.
Published: (2025)
by: Liu, Ruohong, et al.
Published: (2025)
An IoT Framework for Building Energy Optimization Using Machine Learning-based MPC
by: Morteza, Aryan, et al.
Published: (2024)
by: Morteza, Aryan, et al.
Published: (2024)
Physics-Informed Neural Networks for Accelerating Power System State Estimation
by: Falas, Solon, et al.
Published: (2023)
by: Falas, Solon, et al.
Published: (2023)
Learning Dissipative Neural Dynamical Systems
by: Xu, Yuezhu, et al.
Published: (2023)
by: Xu, Yuezhu, et al.
Published: (2023)
A Statistical Decision-Theoretical Perspective on the Two-Stage Approach to Parameter Estimation
by: Lakshminarayanan, Braghadeesh, et al.
Published: (2022)
by: Lakshminarayanan, Braghadeesh, et al.
Published: (2022)
Compact Model Parameter Extraction via Derivative-Free Optimization
by: Martinez, Rafael Perez, et al.
Published: (2024)
by: Martinez, Rafael Perez, et al.
Published: (2024)
Tempering the Bayes Filter towards Improved Model-Based Estimation
by: van Zutphen, Menno, et al.
Published: (2025)
by: van Zutphen, Menno, et al.
Published: (2025)
Building Hybrid B-Spline And Neural Network Operators
by: Romagnoli, Raffaele, et al.
Published: (2024)
by: Romagnoli, Raffaele, et al.
Published: (2024)
Similar Items
-
GenTL: A General Transfer Learning Model for Building Thermal Dynamics
by: Raisch, Fabian, et al.
Published: (2025) -
Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts
by: Raisch, Fabian, et al.
Published: (2025) -
Thermal-GEMs: Generalized Models for Building Thermal Dynamics
by: Koch, Felix, et al.
Published: (2026) -
BUILDA: A Thermal Building Data Generation Framework for Transfer Learning
by: Krug, Thomas, et al.
Published: (2025) -
BuilDyn: Excitation-Driven Data Generation for Building Thermal Dynamics Modeling and Control
by: Koch, Felix, et al.
Published: (2026)