5 papers
The Uncertain Policy Price of Scaling Direct Air Capture
Leonardo Chiani, Pietro Andreoni, Laurent Drouet +4
Direct air carbon capture and storage (DACCS) is a promising CO2 removal technology, but its deployment at scale remains speculative. Yet, its technological, economic, and policy-r…
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…
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…
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…
Variational Inference for Semiparametric Bayesian Novelty Detection in Large Datasets
Luca Benedetti, Eric Boniardi, Leonardo Chiani +4
After being trained on a fully-labeled training set, where the observations are grouped into a certain number of known classes, novelty detection methods aim to classify the instan…