35 citations · 205 across the 22 of their papers we have counts for
6 papers · 1 filter
Score Matched Neural Exponential Families for Likelihood-Free Inference
Lorenzo Pacchiardi, Ritabrata Dutta
Bayesian Likelihood-Free Inference (LFI) approaches allow to obtain posterior distributions for stochastic models with intractable likelihood, by relying on model simulations. In A…
High-resolution Probabilistic Precipitation Prediction for use in Climate Simulations
Sherman Lo, Peter Watson, Peter Dueben +1
The accurate prediction of precipitation is important to allow for reliable warnings of flood or drought risk in a changing climate. However, to make trust-worthy predictions of pr…
Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning
Ritabrata Dutta, Karim Zouaoui-Boudjeltia, Christos Kotsalos +6
Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffec…
TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall
Rilwan Adewoyin, Peter Dueben, Peter Watson +2
Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and strong precipitation events. However, these numerical simulators have difficulties r…
Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic
Ritabrata Dutta, Susana Gomes, Dante Kalise +1
A mathematical model for the COVID-19 pandemic spread, which integrates age-structured Susceptible-Exposed-Infected-Recovered-Deceased dynamics with real mobile phone data accounti…
Anomalous Platelet Transport & Fat-Tailed Distributions
Christos Kotsalos, Karim Zouaoui Boudjeltia, Ritabrata Dutta +2
The transport of platelets in blood is commonly assumed to obey an advection-diffusion equation. Here we propose a disruptive view, by showing that the random part of their velocit…