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Carlos Rodriguez-Pardo

3 papers indexed

arxivcs.LG2026-07-03

Understanding electricity consumption behaviour through Inverse Reinforcement Learning

Enrico Cofler, Carlos Rodriguez-Pardo, Matteo Giuliani, Andrea Castelletti, Massimo Tavoni

Understanding how households consume electricity in response to socioeconomic and climatic drivers is important for decision-makers designing energy policies in a changing climate and under geopolitical tensions. Consumers respond differently to thermal stress depending on income…

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arxivcs.LGcs.AIecon.GNphysics.ao-ph2026-07-03

A harmonised dataset for Earth system foundation models

Carlos Rodriguez-Pardo, Massimo Tavoni

Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human systems that both drive and respond to environmental change. The lack of a unified global training resource that combines climate,…

Also available via: Nature Portfolio

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