6 papers · 1 filter
Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections
Jacopo Ghirri, Carlos Rodriguez-Pardo, Lara Aleluia Reis +1
The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with this ambition remains uncertain.…
TerraNova: A Foundation Model for the Anthropocene
Carlos Rodriguez-Pardo, Massimo Tavoni
A defining problem of the Anthropocene is to model the physical Earth and human societies as one coupled system, yet no learned representation spans their observational breadth. We…
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 re…
Understanding electricity consumption behaviour through Inverse Reinforcement Learning
Enrico Cofler, Carlos Rodriguez-Pardo, Matteo Giuliani +2
Understanding how households consume electricity in response to socioeconomic and climatic drivers is important for decision-makers designing energy policies in a changing climate…
Neural Conditional Transport Maps
Carlos Rodriguez-Pardo, Leonardo Chiani, Emanuele Borgonovo +1
We present a neural framework for learning conditional optimal transport (OT) maps between probability distributions. Our approach introduces a conditioning mechanism capable of pr…
Net-Zero: A Comparative Study on Neural Network Design for Climate-Economic PDEs Under Uncertainty
Carlos Rodriguez-Pardo, Louis Daumas, Leonardo Chiani +1
Climate-economic modeling under uncertainty presents significant computational challenges that may limit policymakers' ability to address climate change effectively. This paper exp…