Concept

Fundamental rights

Related publications (32)

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, Thijs Vogels, Jibril Albachir Frej, Malika Satayeva

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 ...

New York2023

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

Urban living, mobility & health – the future of our cities

Anna Karla De Almeida Milani

The Covid-19 pandemic brought to light the social inequalities and exposed frailties in the access to certain fundamental human rights, such as access to health and mobility. The type of housing, sanitation level, mobility, and urban structures play an ess ...

2021

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 ...

2021

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

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