Publications related to Structural estimation for route choice models considering link specificity of measurement error variances

Orchestrating chromosome conformation capture analysis with Bioconductor

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

2024

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

John Martin Kolinski, Chenzhuo Li, Xinyue Wei

This data package supports the publication 'Complexity of crack front geometry enhances toughness of brittle solids' by Xinyue Wei, Chenzhuo Li, Cían McCarthy, and John M. Kolinski Nature physics (2024) - https://doi.org/10.1038/s41567-024-02435-x DOI: 1 ...

Zenodo2024

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Delphine Ribes Lemay, Nicolas Henchoz, Emily Clare Groves, Margherita Motta

Despite the widespread use of self-tracking technologies for promoting personal wellbeing, there is limited research on the monitoring of intimate data, particularly urine. To shed light on the design possibilities within this unexplored domain we designed ...

2024

Search for the lepton flavour violating decays B0 -> emu and B0s -> emu with LHCb Run 2 data

Sebastian Schulte

A large variety of new physics models suggest that the rates for lepton flavour violating

b

-hadron decays may be much higher than predicted in the Standard Model, which leads to a high interest in the search for such decays. This thesis presents the sear ...

EPFL2024

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Paride Passelli

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

EPFL2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Thomas Alois Weber

A user’s benefit from the energy stored in a battery over its lifetime depends on the time-varying characteristics of the battery, which are in turn affected by the chosen usage behavior. Both the capacity shrinkage and the number of lifetime cycles are st ...

2024

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Fabio Nobile, Thomas Simon Spencer Trigo Trindade

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

2024

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Structural estimation for route choice models considering link specificity of measurement error variances

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Orchestrating chromosome conformation capture analysis with Bioconductor

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Search for the lepton flavour violating decays B0 -> emu and B0s -> emu with LHCb Run 2 data

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Robust machine learning for neuroscientific inference

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Extensions of Peer Prediction Incentive Mechanisms

Orchestrating chromosome conformation capture analysis with Bioconductor

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Search for the lepton flavour violating decays B0 -> emu and B0s -> emu with LHCb Run 2 data

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Robust machine learning for neuroscientific inference

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Extensions of Peer Prediction Incentive Mechanisms