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20222026
most citedHeat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble

2 citations · 2 across the 4 of their papers we have counts for

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cs.LG2026

A Deep Learning Framework for Heat Demand Forecasting using Time-Frequency Representations of Decomposed Features

Adithya Ramachandran, Satyaki Chatterjee, Thorkil Flensmark B. Neergaard +3

District Heating Systems are essential infrastructure for delivering heat to consumers across a geographic region sustainably, yet efficient management relies on optimizing diverse…