Publication

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Publications associées (29)

Euclid preparation XXIV. Calibration of the halo mass function in λ(ν)CDM cosmologies

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel, Maurizio Martinelli, Slobodan Ilic, Yi Wang, Fabio Finelli, Marcello Farina

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quanti ...

EDP SCIENCES S A2023

Fast correlation function calculator A high-performance pair-counting toolkit

Cheng Zhao

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

EDP SCIENCES S A2023

Risk of incorrect choices due to uncertainty in BPS evaluations of conceptual-stage neighbourhood-scale building designs

Marilyne Andersen, Luisa Pastore, Minu Agarwal

At the conceptual stage, building performance simulation (BPS) based evaluations are being increasingly used for tasks such as ranking of competing massing design proposals. However, such conceptual stage evaluations suffer from information deficiency in b ...

2023

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Olga Fink, Luca Biggio

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability impr ...

2023

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

Reto Georg Trappitsch

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

ELSEVIER2023

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...

Zenodo2023

Uncertainty Quantification by Multilevel Monte Carlo and Local Time-Stepping for Wave Propagation

Fabio Nobile

Because of their robustness, efficiency, and non intrusiveness, Monte Carlo methods are probably the most popular approach in uncertainty quantification for computing expected values of quantities of interest. Multilevel Monte Carlo (MLMC) methods signific ...

2022

Measuring the effective thermal resistance of ventilated air-spaces behind common wall assemblies: Theoretical uncertainty analysis and recommendations for the hot box method modifications (ASHRAE 1759-RP)

Dolaana Khovalyg, Mohammad Rahiminejad

A well-designed ventilated wall that incorporates air-space behind cladding can reduce energy use for conditioning buildings by adding a thermally resistive layer. The scarcity of thermal performance data and standardized test methods is a particular barri ...

2022

High-order geometric integrators for nonadiabatic molecular quantum dynamics and their applications to explore conical intersections

Seonghoon Choi

Accurate simulations of molecular quantum dynamics are crucial for understanding numerous natural processes and experimental results. Yet, such high-accuracy simulations are challenging even for relatively simple systems where the Born-Oppenheimer approxim ...

EPFL2022