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Drivers of variability in energy consumption

, , , , and . Submitted for review to European Conference on Machine Learning, (2013)

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Towards Physics-informed Deep Learning for Turbulent Flow Prediction., , , , and . CoRR, (2019)Building dynamic thermal profiles of energy consumption for individuals and neighborhoods., and . IEEE BigData, page 723-728. IEEE Computer Society, (2013)Towards Physics-informed Deep Learning for Turbulent Flow Prediction., , , , and . KDD, page 1457-1466. ACM, (2020)Finding the Right Consumers for Thermal Demand-Response: An Experimental Evaluation., and . IEEE Trans. Smart Grid, 9 (2): 564-572 (2018)Modeling Mountain Snowpack Dynamics with CGANS: A Validation Study., , and . IGARSS, page 3995-3998. IEEE, (2020)Modeling Urbanization Patterns with Generative Adversarial Networks., , , and . IGARSS, page 2095-2098. IEEE, (2018)Segmenting consumers using smart meter data., , and . BuildSys@SenSys, page 49-50. ACM, (2011)Strategic scheduling of residential energy consumers., and . CDC, page 3260-3265. IEEE, (2015)Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems., , , , , and . J. Comput. Phys., (2020)Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale., , and . KDD, page 1357-1366. ACM, (2017)