Publications associées à Loi de mélange

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

CONVERGENCE AND NONCONVERGENCE OF SCALED SELF-INTERACTING RANDOM WALKS TO BROWNIAN MOTION PERTURBED AT EXTREMA

Thomas Mountford

We use generalized Ray-Knight theorems, introduced by B. Toth in 1996, together with techniques developed for excited random walks as main tools for establishing positive and negative results concerning convergence of some classes of diffusively scaled sel ...

Inst Mathematical Statistics-Ims2023

Two statistical regimes in the transition to filamentation

Debbie Eeltink

We experimentally investigate fluctuations in the spectrum of ultrashort laser pulses propagating in air, close to the critical power for filamentation. Increasing the laser peak power broadens the spectrum while the beam approaches the filamentation regim ...

Optica Publishing Group2023

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Ali H. Sayed, Virginia Bordignon, Stefan Vlaski

This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dynamics of Dual-Mode Bedload Transport With Three-Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis

Mehrdad Kiani Oshtorjani, Zhipeng Li, Yong Zhang

Bedload transport often exhibits dual-mode behavior due to interactions of spatiotemporal controlling factors with the migrating three-dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and cluste ...

AMER GEOPHYSICAL UNION2023

Comparison of Responses to DCN vs. VCN Stimulation in a Mouse Model of the Auditory Brainstem Implant (ABI)

Stéphanie Lacour, Florent-Valéry Coen, Nicolas Vachicouras

The auditory brainstem implant (ABI) is an auditory neuroprosthesis that provides hearing to deaf patients by electrically stimulating the cochlear nucleus (CN) of the brainstem. Whether such stimulation activates one or the other of the CN's two major sub ...

SPRINGER2022

A mixture model to take into account diluted gas in liquid flow: applications to aluminium electrolysis

Emile Tryphon Pierre Soutter

Aluminium is a metal sought in the industry because of its various physical properties. It is produced by an electrolysis reduction process in large cells. In these cells, a large electric current goes through the electrolytic bath and the liquid aluminium ...

EPFL2022

System and methods for differential imaging using a lock-in camera

Christophe Moser, Timothé Laforest, Damien Claude-Marie Loterie, Chiara Bonati

The present invention describes an imaging system that allows visualization of a wide range of samples both in terms of morphology and in terms of material (e.g. density distribution, varying chemical composition, or anything that induces a change of optic ...

2021

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

The Impact of Changes in Resolution on the Persistent Homology of Images

Adélie Eliane Garin

Digital images enable quantitative analysis of material properties at micro and macro length scales, but choosing an appropriate resolution when acquiring the image is challenging. A high resolution means longer image acquisition and larger data requiremen ...

IEEE2021

Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking

Mathieu Salzmann, Fatemehsadat Saleh

Despite the recent advances in multiple object tracking (MOT), achieved by joint detection and tracking, dealing with long occlusions remains a challenge. This is due to the fact that such techniques tend to ignore the long-term motion information. In this ...

IEEE COMPUTER SOC2021

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Giuseppe Carleo, Riccardo Rossi, Dian Wu

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

AMER PHYSICAL SOC2021

A mixture model for a dilute dispersion of gas in a liquid flow: Mathematical analysis and application to aluminium electrolysis

Jacques Rappaz, Marco Picasso, Emile Tryphon Pierre Soutter

A mixture model to take into account the flow of small carbon dioxide bubbles dissolved in a liquid is presented. The model describes the evolution of the velocity fields (mixture and gas), the pressure and the volume fraction of gas. The system of equatio ...

2021

Partition and Code: learning how to compress graphs

Andreas Loukas, Michael Bronstein, Nikolaos Karalias, Georgios Bouritsas

Can we use machine learning to compress graph data? The absence of ordering in graphs poses a significant challenge to conventional compression algorithms, limiting their attainable gains as well as their ability to discover relevant patterns. On the other ...

2021

Atomic subgraphs and the statistical mechanics of networks

Sofia Charlotta Olhede

We develop random graph models where graphs are generated by connecting not only pairs of vertices by edges, but also larger subsets of vertices by copies of small atomic subgraphs of arbitrary topology. This allows for the generation of graphs with extens ...

2021

Fast Multi-Step Critiquing for VAE-based Recommender Systems

Boi Faltings, Diego Matteo Antognini

Recent studies have shown that providing personalized explanations alongside recommendations increases trust and perceived quality. Furthermore, it gives users an opportunity to refine the recommendations by critiquing parts of the explanations. On one han ...

ASSOC COMPUTING MACHINERY2021

Context-Aware Learning for Generative Models

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Serafeim Perdikis

This work studies the class of algorithms for learning with side-information that emerges by extending generative models with embedded context-related variables. Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum- ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles

Rico Krüger

This paper i) compares parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian logit models and ii) applies these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV ...

2020

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Daniel Maria Busiello, Deepak Gupta

We consider a general discrete state-space system with both unidirectional and bidirectional links. In contrast to bidirectional links, there is no reverse transition along the unidirectional links Herein, we first compute the statistical length and the th ...

2020

First observation of spalling in tantalum at high temperatures induced by high energy proton beam impacts

Philippe Spätig, Elvis Fornasiere, Marco Calviani

Spalling in tantalum has been observed in an experiment aiming at testing an antiproton production target prototype at CERN’s HiRadMat Facility. The experiment consisted in impacting 47 intense and high-energy proton beams onto a target equipped with ten c ...

2020