Concept

Probabilité a posteriori

Publications associées (279)

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The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Probabilité a posteriori

Graph Chatbot

Chattez avec Graph Search

Pairwise Comparisons with Flexible Time-Dynamics

Generalized maximum entropy estimation

Particle transport at arbitrary timescales with Poisson-distributed collisions

Bayesian Uncertainty Quantification of Physical Models in Thermal-Hydraulics System Codes

Comparing methodologies for structural identification and fatigue life prediction of a highway bridge

Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Expectation propagation in the large data limit

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient

Pairwise Comparisons with Flexible Time-Dynamics

Bayesian Uncertainty Quantification of Physical Models in Thermal-Hydraulics System Codes

Comparing methodologies for structural identification and fatigue life prediction of a highway bridge

Generalized maximum entropy estimation

Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Particle transport at arbitrary timescales with Poisson-distributed collisions

Expectation propagation in the large data limit

Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient