RESCAST-100K is a large-scale benchmark dataset of simulated and real residential energy data for cross-domain load and temperature forecasting.
Gentl: A general transfer learning model for building thermal dynamics
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
The ThermBuild dataset supplies real and simulated 15-minute thermal data from 960 residential buildings for data-driven modeling of heating systems and indoor climate.
BuilDyn supplies customizable excitation strategies and sampling tools to produce control-oriented datasets for machine learning models of building thermal dynamics.
citing papers explorer
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RESCAST-100K: A Comprehensive Dataset for Cross-Domain Residential Load and Indoor Temperature Forecasting
RESCAST-100K is a large-scale benchmark dataset of simulated and real residential energy data for cross-domain load and temperature forecasting.
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Real-world and simulated thermal data from 960 residential multi-zone buildings in Central Europe
The ThermBuild dataset supplies real and simulated 15-minute thermal data from 960 residential buildings for data-driven modeling of heating systems and indoor climate.
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BuilDyn: Excitation-Driven Data Generation for Building Thermal Dynamics Modeling and Control
BuilDyn supplies customizable excitation strategies and sampling tools to produce control-oriented datasets for machine learning models of building thermal dynamics.