Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow

Deep Residual Learning for Image Recognition

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Adam: A Method for Stochastic Optimization

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Identity mappings in deep residual networks

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Large-Scale Machine Learning with Stochastic Gradient Descent

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United Nations Environment Programme

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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction

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Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

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Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis

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Machine learning applications in urban building energy performance forecasting: A systematic review

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From concept to application: A review of use cases in urban building energy modeling

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Applications of artificial intelligence in engineering and manufacturing: a systematic review

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Machine learning for spatial analyses in urban areas: a scoping review

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Data-driven Urban Energy Simulation (DUE-S): Integrating machine learning into an urban building energy simulation workflow

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Exploring the Integration of Simulation and Deep Learning Models for Urban Building Energy Modeling and Retrofit Analysis

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A scalable and efficient framework for city-scale building energy modeling with microclimate considerations

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A framework for augmenting simulation-based building energy models with earth-observational microclimate data products using machine learning predictionsPreprint

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Construction and Research of a Data-Driven Energy Consumption Evaluation Model for Urban Building Operation

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Urban Building Energy Modeling using Deep Learning: A Scalable Approach for Data-Driven Decision-MakingPreprint

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Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional NetworkPreprint

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Advancing Urban Building Energy Modeling: The Role of Hybrid Energy Modeling in Enhancing Energy Consumption Predictions

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A Framework for Augmenting Simulation-Based Building Energy Models with Earth Observational Microclimate Data Using Machine Learning Predictions

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Urban Building Energy Modeling: A Time-Series Building Energy Consumption Use Simulation Prediction Tool Based on Graph Neural Network

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