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Rendering procedural textures for huge digital worlds
The management of huge amounts of 3D data is a serious issue in graphics applications, as in media production. In a classical production pipeline, rendering the 3D scene is processed separately from the generation of textures which represent its visual details. Our project is concerned with treating procedural texture synthesis and photo-realistic rendering as one tightly coupled entity.
The last european old-growth (“subnatural”) fir-BEech forests: a loNg-term and global stuDy for their better understandIng, conServation and management
The last European old-growth (“subnatural”) fir-BEech forests: a loNg-term and global stuDY for their better understanding, conServation and management
Multiscale modelling of solvent phases for solvent extraction
The aim is to optimize and predict the recycling of rare earths, which are strategic metals, by developing a new modeling methodology.
Interdependent Dynamics of EArthquake-prone fault Systems
Interdependent Dynamics of EArthquake-prone fault Systems
Stabilization process in marine surface robotics inspired by swimming snakes
A new generation of robots inspired by the swimming of aquatic snakes has recently emerged in academic contexts. Thanks to their exceptional manoeuvrability, they could intervene urgently in complex situations. However, despite this potential, their surface stability is too precarious. The SSSNAEQ project aims to remove the scientific barriers to surface instability by taking inspiration from snakes,
Phosphorus sequestration: contribution of magnetotactic bacteria in oxic–anoxic transition zones
The project stems from our recent demonstration that a group of magnetotactic bacteria strongly accumulate P at the oxic-anoxic interface in the water column of the ferruginous Lake Pavin (Massif Central, France; Rivas-Lamelo et al. 2017, Geochem. Persp. Lett.). These bacteria constitute a new and relevant model for studying the cycling of P by microorganisms in freshwater environments, the molecular mechanisms of P sequestration and their influence by environmental parameters.
Distributed adaptation and learning over graph signals
The objective of the DARLING project is to propose new adaptive, distributed and collaborative learning methods on high-dimensional dynamic graphs in order to extract structured information from the data streams acquired or transiting at the nodes of these graphs. These methods are confronted with two state-of-the-art observation techniques operating at extreme scales: radio astronomy with the SKA instrument and brain imaging by magnetoencephalography.
Extremal Regression with Applications to Econometrics, Environment and Finance
First, the investigation of mathematical properties under frontier models is often a lot harder than under the standard regression models. Second, while the extreme value properties of quantiles are well developed, much less is known about their expectile and extremile analogues. Third, the problem of estimating conditional extremes and risk measures in high dimensions has been much less discussed in the literature. Our project tries to solve <br />these issues in different directions.
Toulouse Graduate School défis en économie et sciences sociales quantitatives
successful multi-disciplinary Summer School since 2021 organized by IAST and launch of two new multi-d [...] debates as well as the Common Good Summit since 2021; (14) new research partnerships and successful
Réseau d'Innovation sur les Voies de Signalisation en Sciences de la Vie
2021 was marked by the real start of the Labex extension project with the recruitments process of Chairs [...] N : Labex website 206 pages (13 pages added in 2021), participation to scientific popularization in
