Publications related to Adaptive Monte Carlo applied to uncertainty estimation in five axis machine tool link errors identification with thermal disturbance

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Thomas Jean-François Ligonnet, Axel Guy Marie Laureau

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan, Parham Saremi

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Nikita Durasov, Minh Hieu Lê, Nik Joel Dorndorf

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

2024

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Lausanne2024

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Giacomo Garegnani

In this thesis we explore uncertainty quantification of forward and inverse problems involving differential equations. Differential equations are widely employed for modeling natural and social phenomena, with applications in engineering, chemistry, meteor ...

EPFL2021

Modelling the Intracellular Environment under Uncertainty, from Post-translational Modification to Metabolic Networks

Robin Alexander Denhardt-Eriksson

Modelling and analysis of biological systems is crucial in order to quantitatively explain and predict their behaviour. The importance of modelling in systems biology becomes even more evident when tackling complex, large systems. Approaches that rely on ...

EPFL2021

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Lubna Dada

Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, ...

2021

Identification of optimal measurement points for energy monitoring of industrial processes: The case of milk powder production

Meaningful energy analysis of industrial processes requires the installation of energy monitoring systems. However, a lack of systematic methods for identifying the required measurement points, joint to scarce information on the related benefits, results i ...

ELSEVIER SCI LTD2021

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays

Violaine Bellée

This work proposes a method to measure the photon polarisation in

B^+ \rightarrow K^+ \pi^- \pi^+ \gamma

decays and prepares the necessary elements for this measurement using the data sets collected by the LHCb experiment at CERN in

2011

,

2012

, $2016 ...

EPFL2020

Uncertainty propagation for the design study of the PETALE experimental programme in the CROCUS reactor

Andreas Pautz, Vincent Pierre Lamirand, Dimitri Rochman, Axel Guy Marie Laureau

The PETALE experimental programme in the CROCUS reactor intends to provide integral measurements to constrain stainless steel nuclear data. This article presents the tools and the methodology developed to design and optimize the experiments, and its operat ...

2020

Adaptive Monte Carlo applied to uncertainty estimation in five axis machine tool link errors identification with thermal disturbance

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Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Toward Reliable Human Pose Forecasting With Uncertainty

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Modelling the Intracellular Environment under Uncertainty, from Post-translational Modification to Metabolic Networks

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Identification of optimal measurement points for energy monitoring of industrial processes: The case of milk powder production

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays

Uncertainty propagation for the design study of the PETALE experimental programme in the CROCUS reactor

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Toward Reliable Human Pose Forecasting With Uncertainty

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Uncertainty propagation for the design study of the PETALE experimental programme in the CROCUS reactor

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays

Identification of optimal measurement points for energy monitoring of industrial processes: The case of milk powder production

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Modelling the Intracellular Environment under Uncertainty, from Post-translational Modification to Metabolic Networks