24 citations · 87 across the 18 of their papers we have counts for
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Prob-GParareal: A Probabilistic Numerical Parallel-in-Time Solver for Differential Equations
Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
We introduce Prob-GParareal, a probabilistic extension of the GParareal algorithm designed to provide uncertainty quantification for the Parallel-in-Time (PinT) solution of (ordina…
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks
Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
Parallel-in-time (PinT) techniques have been proposed to solve systems of time-dependent differential equations by parallelizing the temporal domain. Among them, Parareal computes…
Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation
Adeline Samson, Massimiliano Tamborrino, Irene Tubikanec
The stochastic FitzHugh-Nagumo (FHN) model is a two-dimensional nonlinear stochastic differential equation with additive degenerate noise, whose first component, the only one obser…
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers
Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
With the advent of supercomputers, multi-processor environments and parallel-in-time (PinT) algorithms offer ways to solve initial value problems for ordinary and partial different…
Guided sequential ABC schemes for intractable Bayesian models
Umberto Picchini, Massimiliano Tamborrino
Sequential algorithms such as sequential importance sampling (SIS) and sequential Monte Carlo (SMC) have proven fundamental in Bayesian inference for models not admitting a readily…
Spectral Density-Based and Measure-Preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs
Evelyn Buckwar, Massimiliano Tamborrino, Irene Tubikanec
Approximate Bayesian Computation (ABC) has become one of the major tools of likelihood-free statistical inference in complex mathematical models. Simultaneously, stochastic differe…