2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2024
From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption
Shourya Bose, Yijiang Li, Amy Van Sant +2
Accurate short-term energy consumption forecasting for commercial buildings is crucial for smart grid operations. While smart meters and deep learning models enable forecasting usi…
cs.LG2024★ 2 cited
Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers
Shourya Bose, Yu Zhang, Kibaek Kim
The advent of smart meters has enabled pervasive collection of energy consumption data for training short-term load forecasting models. In response to privacy concerns, federated l…
cs.CR2023
Privacy-Preserving Load Forecasting via Personalized Model Obfuscation
Shourya Bose, Yu Zhang, Kibaek Kim
The widespread adoption of smart meters provides access to detailed and localized load consumption data, suitable for training building-level load forecasting models. To mitigate p…