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stat.CO2025
gsaot: an R package for Optimal Transport-based sensitivity analysis
Leonardo Chiani, Emanuele Borgonovo, Elmar Plischke +1
gsaot is an R package for Optimal Transport-based global sensitivity analysis. It provides a simple interface for indices estimation using a variety of state-of-the-art Optimal Tra…
cs.LG2025
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…
cs.LG2025
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…