Publications related to Fundamental rights

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks

Martin Jaggi, Mary-Anne Hartley, Vinitra Swamy, Thierry Bossy, Tanja Christina Käser Jacober, Thijs Vogels, Malika Satayeva, Jibril Albachir Frej

Predicting multiple real-world tasks in a single model often requires a particularly diverse feature space. Multimodal (MM) models aim to extract the synergistic predictive potential of multiple data types to create a shared feature space with aligned sema ...

2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Carmela González Troncoso, Bogdan Kulynych

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

Engineering extracellular electron transfer for enhanced energy harvesting in microbial electrochemical devices

Mohammed Mouhib

Microorganisms known as exoelectrogens evolved the ability of transporting electrons across insulating biological membranes. In a physiological context, this enables respiration on extracellular electron acceptors and electron transfer to other organisms. ...

EPFL2023

Mental data protection and the GDPR

Marcello Ienca

Although decoding the content of mental states is currently unachievable, technologies such as neural interfaces, affective computing systems, and digital behavioral technologies enable increasingly reliable statistical associations between certain data pa ...

OXFORD UNIV PRESS2022

Optimization methods for collaborative learning

Sai Praneeth Reddy Karimireddy

A traditional machine learning pipeline involves collecting massive amounts of data centrally on a server and training models to fit the data. However, increasing concerns about the privacy and security of user's data, combined with the sheer growth in the ...

EPFL2021

The concept of the mobilized domain: how it can explain and predict the forces exerted by a cohesive granular avalanche on an obstacle

Christophe Ancey, Johan Alexandre Philippe Gaume, Betty Sovilla, Michael Lukas Kyburz

The calculation of the impact pressure on obstacles in granular flows is a fundamental issue of practical relevance, e.g. for snow avalanches impacting obstacles. Previous research shows that the load on the obstacle builds up, due to the formation of forc ...

2022

Language Resources for Historical Newspapers: the Impresso Collection

Maud Ehrmann, Matteo Romanello, Raphaël Barman

Following decades of massive digitization, an unprecedented amount of historical document facsimiles can now be retrieved and accessed via cultural heritage online portals. If this represents a huge step forward in terms of preservation and accessibility, ...

European Language Resources Association2020

The RECIPE approach to challenges in deeply heterogeneous high performance systems

David Atienza Alonso, Marina Zapater Sancho

RECIPE (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems) is a recently started project funded within the H2020 FETHPC programme, which is expressly targeted at exploring new High-Performance Computing (HPC) ...

ELSEVIER2020

Fundamental Limits for Implanted Antennas: Maximum Power Density Reaching Free Space

Anja Skrivervik, Zvonimir Sipus

Medical implants with communication capability are becoming increasingly popular with today’s trends to continuously monitor patient’s condition. This is a major challenge for antenna designers since the implants are inherently small and placed in a commun ...

2019

Pedestrian Image Generation for Self-driving Cars

Alexandre Massoud Alahi, Saeed Saadatnejad

Pedestrian image generation in the desired pose can be used in a wide range of applications e.g., person re-identification and tracking which are among the fundamental challenges in self-driving cars. This is a hard task because it should be invariant to a ...

2019

A Weak Form Implementation of Nonlinear Axisymmetric Shell Equations With Examples

Pedro Miguel Nunes Pereira de Almeida Reis, Matteo Pezzulla

We present a weak form implementation of the nonlinear axisymmetric shell equations. This implementation is suitable to study the nonlinear deformations of axisymmetric shells, with the capability of considering a general mid-surface shape, non-homogeneous ...

2019

The Impact of RDMA on Agreement

Rachid Guerraoui, Mihail Igor Zablotchi, Naama Ben David

Remote Direct Memory Access (RDMA) is becoming widely available in data centers. This technology allows a process to directly read and write the memory of a remote host, with a mechanism to control access permissions. In this paper, we study the fundamenta ...

2019

Learning nuisances to track pedestrians in autonomous vehicles

Alexandre Massoud Alahi, George Adaimi

Autonomous vehicles rely on an accurate perception module. One of the fundamental challenges is to efficiently track pedestrians surrounding a vehicle to anticipate risky situations. Over the past decades, researchers have formulated the tracking problem a ...

2018

The Resilience of Sustainability Transitions

Claudia Rebeca Binder Signer, Romano Tobias Wyss

Finding ways to understand, analyze, and manage sustainability transitions is a fundamental challenge for sustainability science. In this paper, we show how we can substantially deepen our understanding of factors that determine the success of sustainabili ...

2018

On the debris-level origins of adhesive wear

Jean-François Molinari, Ramin Aghababaei, Derek Warner

Every contacting surface inevitably experiences wear. Predicting the exact amount of material loss due to wear relies on empirical data and cannot be obtained from any physical model. Here, we analyze and quantify wear at the most fundamental level, i.e., ...

Natl Acad Sciences2017

Microstructure informed tractography: pitfalls and open challenges

Jean-Philippe Thiran, Alessandro Daducci, Maxime Descoteaux

One of the major limitations of diffusion MRI tractography is that the fiber tracts recovered by existing algorithms are not truly quantitative. Local techniques for estimating more quantitative features of the tissue microstructure exist, but their combin ...

Frontiers Research Foundation2016

X-ray spectrometry and imaging for ancient administrative handwritten documents

Giorgio Margaritondo, Frédéric Kaplan, Fauzia Albertin, Marco Stampanoni

‘Venice Time Machine’ is an international program whose objective is transforming the ‘Archivio di Stato’ – 80 km of archival records documenting every aspect of 1000 years of Venetian history – into an open-access digital information bank. Our study is pa ...

Wiley-Blackwell2015

Modeling Brain Circuitry over a Wide Range of Scales

Pascal Fua, Graham Knott

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is nee ...

Frontiers Research Foundation2015

Une fabrique de la société-Monde, Internet entre technique et politique mondiale

Luc Guillemot

The Internet is a place made of worldwide interactions, and as such it is an environment of the World. Its technical specifications gather opposing views concerning relations to the World, which coincide nevertheless in the recognition of fundamental right ...

EPFL2014