4 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Fédérale de Toulouse Midi-PyrénéesFR12 papers
- Université Toulouse III - Paul SabatierFR8 papers
- Institut National des Sciences Appliquées de ToulouseFR6 papers
- Institut de Mathématiques de ToulouseFR5 papers
- Institut de Recherche en Informatique de ToulouseFR4 papers
- Institut Polytechnique de BordeauxFR4 papers
- Université Toulouse-I-CapitoleFR4 papers
- Université Toulouse - Jean JaurèsFR4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Brown UniversityUS2 papers
- Centre de Recherche en Économie et StatistiqueFR2 papers
- Analyse et Traitement Informatique de la Langue FrançaiseFR1 paper
15 papers
Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach
L{é}a Billet, Louise Trav{é}-Massuy{è}s, Elodie Chanthery +1
Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate future anomalies. This work int…
Scalable anomaly detection via a univariate Christoffel function
Florian Grivet, Didier Henrion, Jean-Bernard Lasserre +1
Anomaly detection plays a critical role in identifying unusual patterns across domains such as fraud detection, network intrusion, and system fault diagnosis. Recently, Christoffel…
GLeMM: A large-scale multilingual dataset for morphological research
Hathout Nabil, Basilio Calderone, Fiammetta Namer +1
In derivational morphology, what mechanisms govern the variation in form-meaning relations between words? The answers to this type of questions are typically based on intuition and…
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
Pierre Lotte, André Péninou, Olivier Teste
Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing benchmark datasets. Current resou…
Relation between in vitro microbial fermentations and in vivo performance in pigs selected for their residual feed intake
Olivier Zemb, Lauren Jouaron, Estelle Jordi +10
Bioinformatic analysis of microbiota revealed that certain metabolic pathways are associated with low- and high- residual feed intake (HRFI and LRFI), such as the amino-acid biosyn…
Busemann Functions in the Wasserstein Space: Existence, Closed-Forms, and Applications to Slicing
Clément Bonet, Elsa Cazelles, Lucas Drumetz +1
The Busemann function has recently found much interest in a variety of geometric machine learning problems, as it naturally defines projections onto geodesic rays of Riemannian man…
A modified Crank-Nicolson scheme for the Vlasov-Poisson system with a strong external magnetic field
Francis Filbet, L Miguel Rodrigues, Kim Han Trinh
We propose and study a Particle-In-Cell (PIC) method based on the Crank-Nicolson time discretization for the Vlasov-Poisson system with a strong and inhomogeneous external magnetic…
Sharp asymptotics for the KPP equation with some front-like initial data
Mingmin Zhang
We provide the first PDE proof of the celebrated Bramson's results in 1983 concerning the large time asymptotics for the KPP equation under front-like initial data of types…
Full non-LTE multi-level radiative transfer I. An atom with three bound infinitely sharp levels
Tristan Lagache, Frédéric Paletou, Malali Sampoorna
The standard nonlocal thermodynamic equilibrium (non-LTE) multi-level radiative transfer problem only takes into account the deviation of the radiation field and atomic populations…
On the Wasserstein Geodesic Principal Component Analysis of probability measures
Nina Vesseron, Elsa Cazelles, Alice Le Brigant +1
This paper focuses on Geodesic Principal Component Analysis (GPCA) on a collection of probability distributions using the Otto-Wasserstein geometry. The goal is to identify geodesi…
Sample complexity of optimal transport barycenters with discrete support
Léo Portales, Edouard Pauwels, Elsa Cazelles
Computational implementation of optimal transport barycenters for a set of target probability measures requires a form of approximation, a widespread solution being empirical appro…
Multivariate Self-Exciting Processes with Dependencies
Caroline Hillairet, Thomas Peyrat, Anthony Réveillac
This paper introduces the class of multidimensional self-exciting processes with dependencies (MSPD), which is a unifying writing for a large class of processes: counting, loss, in…
Linear programming for finite-horizon vector-valued Markov decision processes
Anas Mifrani, Dominikus Noll
We propose a vector linear programming formulation for a non-stationary, finite-horizon Markov decision process with vector-valued rewards. Pareto efficient policies are shown to c…
Diagnosing and exploiting the computational demands of videos games for deep reinforcement learning
Lakshmi Narasimhan Govindarajan, Rex G Liu, Drew Linsley +4
Humans learn by interacting with their environments and perceiving the outcomes of their actions. A landmark in artificial intelligence has been the development of deep reinforceme…
Break It Down: Evidence for Structural Compositionality in Neural Networks
Michael A. Lepori, Thomas Serre, Ellie Pavlick
Though modern neural networks have achieved impressive performance in both vision and language tasks, we know little about the functions that they implement. One possibility is tha…