
Using mobility data in the design of optimal lockdown strategies for the COVID19 pandemic in England
A mathematical model for the COVID19 pandemic spread in England is pres...
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Distancelearning For Approximate Bayesian Computation To Model a Volcanic Eruption
Approximate Bayesian computation (ABC) provides us with a way to infer p...
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Bayesian Calibration of Forcefields from Experimental Data: TIP4P Water
Molecular dynamics (MD) simulations give access to equilibrium and/or dy...
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LikelihoodFree Parameter Estimation for Dynamic Queueing Networks
Many complex realworld systems such as airport terminals, manufacturing...
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ABCpy: A HighPerformance Computing Perspective to Approximate Bayesian Computation
ABCpy is a highly modular scientific library for Approximate Bayesian Co...
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Parameter estimation of platelets deposition: Approximate Bayesian computation with high performance computing
A numerical model that quantitatively describes how platelets in a shear...
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Bayesian Inference of Spreading Processes on Networks
Infectious diseases are studied to understand their spreading mechanisms...
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Bayesian Inference of Network Epidemics
Infectious diseases are studied to understand their spreading mechanisms...
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Bayesian inference in hierarchical models by combining independent posteriors
Hierarchical models are versatile tools for joint modeling of data sets ...
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Modellingbased experiment retrieval: A case study with gene expression clustering
Motivation: Public and private repositories of experimental data are gro...
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Classification and Bayesian Optimization for LikelihoodFree Inference
Some statistical models are specified via a data generating process for ...
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Likelihoodfree inference via classification
Increasingly complex generative models are being used across disciplines...
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Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space
We address the problem of retrieving relevant experiments given a query ...
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Ritabrata Dutta
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Swiss National Science Foundation fellow in the InterDisciplinary Institute of Data Science (IDIDS) at USI, and presently working on Statistical Inference on LargeScale Mechanistic Network Models