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Open Computing Infrastructure for Sharing Data Analytics to Support Building Energy Simulations., , , , , , , , , and 2 other author(s). J. Comput. Civ. Eng., (2019)A Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems., , , , and . ACM Trans. Sens. Networks, 14 (3-4): 30:1-30:22 (2018)Urban Building Energy Modeling (UBEM) Tools: A State-of-the-Art Review of bottom-up physics-based approaches., , , and . CoRR, (2021)Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset., , , and . BuildSys@SenSys, page 242-245. ACM, (2022)CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities., , , , , , , , and . BuildSys@SenSys, page 274-275. ACM, (2023)Effective Missing Value Imputation Methods for Building Monitoring Data., , , , , , and . IEEE BigData, page 2866-2875. IEEE, (2020)Privacy-preserving building-related data publication using PAD., , , , and . BuildSys@SenSys, page 32:1-32:2. ACM, (2017)The CityLearn Challenge 2022: Overview, Results, and Lessons Learned., , , , , , , , , and 16 other author(s). NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 85-103. PMLR, (2021)PAD: protecting anonymity in publishing building related datasets., , , , and . BuildSys@SenSys, page 4:1-4:10. ACM, (2017)