Publications associées à Recent advances in trajectory inference from single-cell omics data

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Nikita Durasov, Nik Joel Dorndorf, Minh Hieu Lê

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

2024

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Thomas Jean-François Ligonnet, Axel Guy Marie Laureau

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

Orchestrating chromosome conformation capture analysis with Bioconductor

Cyril Matthey-Doret

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

Nature Research2024

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Asli Sahin

Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...

EPFL2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Networks with correlated edge processes

Mária Süveges, Sofia Charlotta Olhede

This article proposes methods to model non-stationary temporal graph processes motivated by a hospital interaction data set. This corresponds to modelling the observation of edge variables indicating interactions between pairs of nodes exhibiting dependenc ...

OXFORD UNIV PRESS2023

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Hussein Fadl Hassan Hassan Osman

Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Statistical limits of high-dimensional inference problems

Clément Dominique Luneau

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

EPFL2021

Experimental characterisation of textile compaction response: A benchmark exercise

Véronique Michaud, Christophe Lopez, Baris Çaglar

This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure ...

2021

A Pareto Dominance Principle for Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2024

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Giacomo Garegnani

In this thesis we explore uncertainty quantification of forward and inverse problems involving differential equations. Differential equations are widely employed for modeling natural and social phenomena, with applications in engineering, chemistry, meteor ...

EPFL2021

Graph Embeddings for One-pass Processing of Heterogeneous Queries

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong

Effective information retrieval (IR) relies on the ability to comprehensively capture a user's information needs. Traditional IR systems are limited to homogeneous queries that define the information to retrieve by a single modality. Support for heterogene ...

IEEE COMPUTER SOC2020

Modeling biochemical reaction networks in complex intracellular environments

Daniel Robert Weilandt

Whether one aims to design treatments for diseases such as cancer or diabetes, engineer cells to produce valuable biochemicals sustainably, or to grasp the behavior of living organisms, it is essential to understand how cells react to genetic, environmenta ...

EPFL2020

Statistical Physics Methods for Community Detection

Chun Lam Chan

This thesis is devoted to information-theoretic aspects of community detection. The importance of community detection is due to the massive amount of scientific data today that describes relationships between items from a network, e.g., a social network. I ...

EPFL2019

Using an amplitude analysis to measure the photon polarisation in B -> K pi pi gamma decays

Olivier Schneider, Frédéric Blanc, Violaine Bellée, Preema Rennee Pais

A method is proposed to measure the photon polarisation parameter.. in b. s. transitions using an amplitude analysis of B. Kpp. decays. Simplified models of the Kpp system are used to simulate B+. K+ p -p+. and B0. K+ p -p0. decays, validate the amplitude ...

Springer2019

A new clustering and visualization method to evaluate urban heat energy planning scenarios

Jean-Louis Scartezzini, Silvia Coccolo, Dasaraden Mauree, Sara Torabi Moghadam

Spatial visualization is a very useful tool to help decision-makers in the urban planning process, i) to define future energy transition pathways, ii) to implement energy efficiency strategies and iii) to integrate renewable energy technologies in the cont ...

2019

Control Theory Concepts for Modeling Uncertainty in Enzyme Kinetics of Biochemical Networks

Ljubisa Miskovic, Vassily Hatzimanikatis, Georgios Savoglidis, Milenko Tokic

Analysis of the dynamic and steady-state properties of biochemical networks hinges on information about the parameters of enzyme kinetics. The lack of experimental data characterizing enzyme activities and kinetics along with the associated uncertainties i ...

2019

Contributions to Likelihood-Based Modelling of Extreme Values

Léo Raymond-Belzile

xtreme value analysis is concerned with the modelling of extreme events such as floods and heatwaves, which can have large impacts. Statistical modelling can be useful to better assess risks even if, due to scarcity of measurements, there is inherently ver ...

EPFL2019

Training in Mapping Changes on an Archaeological Site

Bertrand Merminod, Pierre-Yves Gilliéron, Jérôme Zufferey

The evolution of technologies makes surveying accessible to a broader community of professionals and students. Therefore, teaching geomatics is a continuous challenge. This article presents an original pedagogical approach based on a teaching unit gatherin ...

2018