Christopher R. Laughman
Orcid: 0000-0002-8540-2249Affiliations:
- Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA
According to our database1,
Christopher R. Laughman
authored at least 29 papers
between 2000 and 2024.
Collaborative distances:
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Bibliography
2024
Power System Modeling for Identification and Control Applications using Modelica and OpenIPSL.
Proceedings of the IEEE Conference on Control Technology and Applications, 2024
Bayesian Forecasting with Deep Generative Disturbance Models in Stochastic MPC for Building Energy Systems.
Proceedings of the IEEE Conference on Control Technology and Applications, 2024
Assessing Building Control Performance Using Physics-Based Simulation Models and Deep Generative Networks.
Proceedings of the IEEE Conference on Control Technology and Applications, 2024
Proceedings of the IEEE Conference on Control Technology and Applications, 2024
2023
Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation.
IEEE Trans. Syst. Man Cybern. Syst., May, 2023
Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States.
IEEE Control. Syst. Lett., 2023
Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints.
CoRR, 2023
Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?
Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023
LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems.
Proceedings of the American Control Conference, 2023
Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles.
Proceedings of the American Control Conference, 2023
2022
CoRR, 2022
Proceedings of the Annual Modeling and Simulation Conference, 2022
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints.
Proceedings of the American Control Conference, 2022
Proceedings of the American Control Conference, 2022
2021
Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins.
CoRR, 2021
ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling.
CoRR, 2021
Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters.
Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021
Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
IEEE Trans. Control. Syst. Technol., 2020
2019
Proceedings of the 13th International Modelica Conference, Regensburg, Germany, 2019
Thermodynamic Property and Fluid Modeling with Modern Programming Language Construct.
Proceedings of the 13th International Modelica Conference, Regensburg, Germany, 2019
Proceedings of the 13th International Modelica Conference, Regensburg, Germany, 2019
Proceedings of the 17th European Control Conference, 2019
Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2019
2018
Proceedings of the IEEE Conference on Control Technology and Applications, 2018
2017
Optimization of circuitry arrangements for heat exchangers using derivative-free optimization.
CoRR, 2017
2007
2006
IEEE Trans. Autom. Control., 2006
2000