Concept

Importance sampling

Related publications (35)

Monte Carlo Estimators for Differential Light Transport

Wenzel Alban Jakob, Tizian Lucien Zeltner, Sébastien Nicolas Speierer

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased metho ...

ASSOC COMPUTING MACHINERY2021

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Fabio Nobile, Sebastian Krumscheid, Matthieu Claude Martin

We consider the numerical approximation of an optimal control problem for an elliptic Partial Differential Equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes the expected ...

2021

Multilevel ensemble Kalman filtering for spatio-temporal processes

Fabio Nobile, Hakon Andreas Hoel

We design and analyse the performance of a multilevel ensemble Kalman filter method (MLEnKF) for filtering settings where the underlying state-space model is an infinite-dimensional spatio-temporal process. We consider underlying models that needs to be si ...

2021

Quantifying uncertain system outputs via the multilevel Monte Carlo method — Part I: Central moment estimation

Fabio Nobile, Sebastian Krumscheid, Michele Pisaroni

In this work we introduce and analyze a novel multilevel Monte Carlo (MLMC) estimator for the accurate approximation of central moments of system outputs affected by uncertainties. Central moments play a central role in many disciplines to characterize a r ...

2020

Probabilistic and deterministic full field approaches to simulate recrystallization in ODS steels

Roland Logé, Flore Villaret

Mechanical and functional properties of Oxide Dispersion Strengthened (ODS) ferritic/martensitic steels are strongly related to their microstructures. Thus, numerical modeling of microstructure evolution during ODS forming is of prime importance. In this w ...

ELSEVIER2020

Quantum Monte Carlo approach to the non-equilibrium steady state of open quantum systems

Alexandra Nagy

Many-body open quantum systems are exposed to an essentially uncontrollable environment that acts as a source of decoherence and dissipation. As the exact treatment of such models is generally unfeasible, it is favourable to formulate an approximate descri ...

EPFL2020

Central limit theorems for multilevel Monte Carlo methods

Sebastian Krumscheid, Hakon Andreas Hoel

In this work, we show that uniform integrability is not a necessary condition for central limit theorems (CLT) to hold for normalized multilevel Monte Carlo (MLMC) estimators and we provide near optimal weaker conditions under which the CLT is achieved. In ...

2019

Phase field parameters for battery compounds from first-principles calculations

In this work, we present and apply schemes to determine from first-principles calculations the relevant effective parameters used in phase field theory simulations of battery compounds. In particular, we derive that a consistent free energy density can be ...

2019

Driven-dissipative quantum Monte Carlo method for open quantum systems

Vincenzo Savona, Alexandra Nagy

We develop a real-time full configuration-interaction quantum Monte Carlo approach to model driven-dissipative open quantum systems with Markovian system-bath coupling. The method enables stochastic sampling of the Liouville–von Neumann time evolution of t ...

2018

Semiparametric Bayesian Risk Estimation for Complex Extremes

Thomas Lugrin

Extreme events are responsible for huge material damage and are costly in terms of their human and economic impacts. They strike all facets of modern society, such as physical infrastructure and insurance companies through environmental hazards, banking an ...

EPFL2018

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