Publications

Optimization and Control

A Framework for Joint Affine and Diffeomorphic Image Registration

Anatomical image registration commonly relies on a sequential pipeline where an affine alignment is estimated first and then held fixed while a non-rigid diffeomorphic deformation is applied. This two-step process often leads to suboptimal results,…

Anton François, Rayane Mouhli, Thomas Pierron

Atmospheric and Oceanic Physics

Feature-Based Machine Learning Framework for Multi-Source NH₃ Dataset Analysis

Accurate monitoring of atmospheric ammonia (NH3) is important for air-quality assessment and sustainable agriculture, but available datasets differ in spatial resolution, temporal coverage, units, and physical meaning. This study presents a feature…

Ata Jahangir Moshayedi, Babar Hussain Shah, Amir Sohail Khan, Seyyed Ali Eftekhari, Amin Kolahdooz, David Bassir

Automation - 2026

Discrete Mathematics

How Not to Tabulate the 2028 US Democratic Primary

The US Democratic Party introduced a novel electoral system in 2020, combining instant runoff voting (IRV) and proportional representation (PR) with a 15% viability threshold. This tabulation system was chosen over more established methods, such as…

Max Dunitz

Machine Learning

Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models

Non-intrusive reduced-order models (NIROMs) have become a standard tool for approximating parametric partial differential equations from computer design of experiments while significantly reducing computational costs. However, assessing the…

Edgar Jaber, Rémy Vallot, Thibault Dairay, Mathilde Mougeot

Computation and Language

Improving Thematic Balance in Press Release Generation with GMMs and Dimensionality Reduction

Large Language Models (LLMs) are widely used to generate high-quality textual content, such as news articles and business reports. However, their performance is highly dependent on the quality and balance of the training data. In real-world…

Imed Keraghel, Mohamed Nadif

2026 International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML 2026) - 2026

Analysis of PDEs

Learning features from Newton's algorithm: a way to accelerate nonlinear parametrized PDE solvers

It is well known that Newton's method converges faster when the initial guess is closer to a root of a system of nonlinear equations. In this paper, a two-stage Newton initial guess strategy is proposed by learning features from a parameter-space…

Rémy Vallot, Florian de Vuyst, Thibault Dairay, Mathilde Mougeot

Image Processing

Theatre Chapbooks At Scale: A Statistical Comparative Analysis of Typography

We propose a statistical methodology that quantifies the similarity of typefaces between printed historical books. This provides a tool that accelerates philological analysis. Using character prototypes derived from clustering and aligning…

Diego Belzarena, Seginus Mowlavi, Paula Casariego Castiñeira, Alejandra Ulla Lorenzo, Gregory Randall, Jean-Michel Morel

Fluid mechanics

Mixing induced by Faraday surface waves

We investigate how surface waves enhance mixing across the interface between two miscible fluids with a small density contrast. Imposing a vertical, time-periodic acceleration, we excite Faraday waves both experimentally and numerically. In systems…

Andrés Castillo-Castellanos, Benoît-Joseph Gréa, Antoine Briard, Louis Gostiaux

Artificial Intelligence

Efficient Neural-Network-Based High-Resolution Radiative Transfer for CO₂ Retrieval, and Application to Interferometric Sensing

Studying climate change requires reducing uncertainties in CO2 and CH4 emission estimates to better distinguish anthropogenic from natural sources, which motivates spaceborne measurements with improved revisit frequency and spatial coverage. In this…

Jordan Lontsi Tedongmo, Yann Ferrec, Laurence Croizé, Pablo Musé, Gabriele Facciolo, Andrés Almansa

Image Processing

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

Optical Character Recognition (OCR) is a key component in the digitization of historical archives. Recently, Vision-Language Models (VLMs) have emerged as strong alternatives to traditional OCR systems, achieving state-of-the-art performance on…

Marina Gardella, Camilo Mariño, Diego Belzarena, Ignacio Ramírez, Gregory Randall, Jean-Michel Morel