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Probabilistic building retrofit for residential buildings
Building retrofit is considered one of the most promising solutions towards improving the environmental footprint of the existing building stock. There exist several methods to identify which building interventions are necessary given some requirements. Recently discriminative machine learning models have been used to compute near-optimal building retrofit solutions. However, such models demand a very large and complete data set for training and they don't perform well in the case of outliers. Generative modeling can overcome those issues and play a key role in building retrofit.
Keywords: building retrofit, machine learning, generative modeling
See attached document.
See attached document.
The goal of this master thesis is to develop a generative model for building retrofit for residential buildings.
The goal of this master thesis is to develop a generative model for building retrofit for residential buildings.