An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data

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Physics-Inspired Structural Representations for Molecules and Materials

Michele Ceriotti, Andrea Grisafi, Félix Benedito Clément Musil

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic-scale structure of matter and its properties, involves transforming the Cartesian coordinates of the atom ...

AMER CHEMICAL SOC2021

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Designing Gamified Activities with Haptic-Enabled Tangible Robots for Therapy and Assistance

Arzu Güneysu Özgür

In this thesis, we contribute to the field of rehabilitation robotics by designing haptic-enabled tangible robot-based activities and exploring their added value for therapy and assistance. The research specifically focuses on the design and development of ...

EPFL2021

Counting People by Estimating People Flows

Pascal Fua, Mathieu Salzmann, Weizhe Liu

Modern methods for counting people in crowded scenes rely on deep networks to estimate people densities in individual images. As such, only very few take advantage of temporal consistency in video sequences, and those that do only impose weak smoothness co ...

2022

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

2021

Improving sample and feature selection with principal covariates regression

Michele Ceriotti, Edgar Albert Engel, Benjamin Aaron Helfrecht

Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...

2021

Multi-Dimensional Explanation of Target Variables from Documents

Boi Faltings, Diego Matteo Antognini, Claudiu-Cristian Musat

Automated predictions require explanations to be interpretable by humans. Past work used attention and rationale mechanisms to find words that predict the target variable of a document. Often though, they result in a tradeoff between noisy explanations or ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Smartphone Sensing for the Well-being of Young Adults: A Review

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Over the years, mobile phones have become versatile devices with a multitude of capabilities due to the plethora of embedded sensors that enable them to capture rich data unobtrusively. In a world where people are more conscious regarding their health and ...

2021

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Francesca Criscuolo, Mandresy Ivan Ny Hanitra

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Daniel Gatica-Perez, Skanda Muralidhar, Lakmal Buddika Meegahapola

Introduction Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. ...

2021

Real-Time Multi-Ion-Monitoring Front-End With Interference Compensation by Multi-Output Support Vector Regressor

Giovanni De Micheli, Sandro Carrara, Francesca Criscuolo, Mandresy Ivan Ny Hanitra

Ion-sensors play a major role in physiology and healthcare monitoring since they are capable of continuously collecting biological data from body fluids. Nevertheless, ion interference from background electrolytes present in the sample is a paramount chall ...

2021