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Publications associées (144)

Extensions of Peer Prediction Incentive Mechanisms

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

From trees to barcodes and back again II: Combinatorial and probabilistic aspects of a topological inverse problem

Kathryn Hess Bellwald, Lida Kanari, Adélie Eliane Garin

In this paper we consider two aspects of the inverse problem of how to construct merge trees realizing a given barcode. Much of our investigation exploits a recently discovered connection between the symmetric group and barcodes in general position, based ...

2024

Certification of Bottleneck Task Assignment With Shortest Path Criteria

Maryam Kamgarpour, Tony Alan Wood

Minimising the longest travel distance for a group of mobile robots with interchangeable goals requires knowledge of the shortest length paths between all robots and goal destinations. Determining the exact length of the shortest paths in an environment wi ...

2023

Interpretable statistical representations of neural population dynamics and geometry

Pierre Vandergheynst, Alexis Arnaudon, Adám Gosztolai

The dynamics of neuron populations during diverse tasks often evolve on low-dimensional manifolds. However, it remains challenging to discern the contributions of geometry and dynamics for encoding relevant behavioural variables. Here, we introduce an unsu ...

2023

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Rachid Guerraoui, Nirupam Gupta, John Stephan, Youssef Allouah, Rafaël Benjamin Pinot

The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...

2023

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

Sara Bonella, Fabio Pietrucci, David Daniel Girardier

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Melville2023

Stochastic particle transport by deep-water irregular breaking waves

Debbie Eeltink

Correct prediction of particle transport by surface waves is crucial in many practical applications such as search and rescue or salvage operations and pollution tracking and clean-up efforts. Recent results by Deike et al. (J. Fluid Mech., vol. 829, 2017, ...

Cambridge2023

Cloud Condensation Nuclei (CCN) concentrations measured in the Swiss container during MOSAiC 2019/2020

Julia Schmale, Ivo Fabio Beck, Benjamin Jérémy Laurent Heutte, Nora Bergner, Hélène Paule Angot, Lubna Dada

This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to Septem ...

EPFL Infoscience2023

Frequency Regulation with Storage: On Losses and Profits

Daniel Kuhn, François Richard Vuille, Dirk Lauinger

Low-carbon societies will need to store vast amounts of electricity to balance intermittent generation from wind and solar energy, for example, through frequency regulation. Here, we derive an analytical solution to the decision-making problem of storage o ...

2023

Preconditioners for robust optimal control problems under uncertainty

Fabio Nobile, Tommaso Vanzan

The discretization of robust quadratic optimal control problems under uncertainty using the finite element method and the stochastic collocation method leads to large saddle-point systems, which are fully coupled across the random realizations. Despite its ...

2022

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