A combined on-the-fly/interpolation procedure for evaluating energy values needed in molecular simulations

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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

Molecular simulation on two-dimensional nanoporous material for energy-efficient separation

Mohammad Tohidivahdat

The energy-consumption by the chemical and petrochemical industry in the European Union (EU) accounts for about quarter of its energy footprint. Approximately half of this energy goes toward chemical separation, currently dominated by thermally-driven pro ...

EPFL2023

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Edoardo Remelli

In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pr ...

EPFL2022

Effects of Degrees of Freedom on Calculating Diffusion Properties in Nanoporous Materials br

Berend Smit, Raffaela Cabriolu, Henglu Xu

If one carries out a molecular simulation ofNparticlesusing periodic boundary conditions, linear momentum is conserved,and hence, the number of degrees of freedom is set to 3N-3. Inmost programs, this number of degrees of freedom is the defaultsetting. How ...

AMER CHEMICAL SOC2022

Adhesive wear with a coarse-grained discrete element model

Jean-François Molinari, Son-Jonathan Pham-Ba

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high computational c ...

ELSEVIER SCIENCE SA2022

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Sundar Subramaniam Ganesh

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

EPFL2022

Efficient and Accurate Physically-Based Differentiable Rendering

Delio Aleardo Vicini

Physically-based rendering algorithms generate photorealistic images of virtual scenes. By simulating light paths in a scene, complex physical effects such as shadows, reflections and volumetric scattering can be reproduced. Over the last decade, physicall ...

EPFL2022

Single photon detection with amorphous silicon-based microchannel plates: A Monte Carlo model

Christophe Ballif, Nicolas Würsch, Jonathan Emanuel Thomet, Janina Christine Isabelle Löffler, Samira Alexandra Frey

Microchannel plates based on amorphous silicon have the inherent capability to overcome the existing spatial and temporal resolution limitations of single photon detectors. A Monte Carlo model-based study is presented here that serves to exploit their full ...

2022

Differentiable Signed Distance Function Rendering

Wenzel Alban Jakob, Delio Aleardo Vicini, Sébastien Nicolas Speierer

Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

ASSOC COMPUTING MACHINERY2022

Differentiable Physically Based Rendering: Algorithms, Systems and Applications

Merlin Eléazar Nimier-David

Physically based rendering methods can create photorealistic images by simulating the propagation and interaction of light in a virtual scene. Given a scene description including the shape of objects, participating media, material properties, etc., the sim ...

EPFL2022

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