Showing 1–20 of 27 results
/ Date/ Name
Dec 6, 2021Physically Consistent Neural Networks for building thermal modeling: theory and analysisApr 24, 2023Stochastic MPC for energy hubs using data driven demand forecastingMar 10, 2022Near-optimal Deep Reinforcement Learning Policies from Data for Zone Temperature ControlNov 23, 2023SIMBa: System Identification Methods leveraging BackpropagationDec 23, 2022Towards Scalable Physically Consistent Neural Networks: an Application to Data-driven Multi-zone Thermal Building ModelsNov 11, 2022Physically Consistent Neural ODEs for Learning Multi-Physics SystemsNov 4, 2020Temporal Resolution of Measurements and the Effects on Calibrating Building Energy ModelsSep 15, 2020Robust MPC with data-driven demand forecasting for frequency regulation with heat pumpsMay 22, 2025Trajectory-Independent Flexibility Envelopes of Energy-Constrained Systems with State-Dependent LossesOct 29, 2021Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPCOct 25, 2021Data-Driven Demand-Side Flexibility Quantification: Prediction and Approximation of Flexibility EnvelopesApr 17, 2026Safe Deep Reinforcement Learning for Building Heating Control and Demand-side FlexibilityNov 26, 2020Input Convex Neural Networks for Building MPCNov 30, 2022Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple RulesFeb 9, 2023Designing Fairness in Autonomous Peer-to-peer Energy TradingJul 4, 2023Degradation-aware data-enabled predictive control of energy hubsApr 8, 2025Plug and Play Distributed Control of Clustered Energy Hub NetworksOct 1, 2025Uncertainty-Aware Flexibility of Buildings: From Quantification to ProvisionApr 9, 2026Towards socio-techno-economic power systems with demand-side flexibilityNov 6, 2023Stable Linear Subspace Identification: A Machine Learning Approach