Les indiens Oyampi de la Guyane Française

Hurault Jean. Les Indiens Oyampi de la Guyane française. In: Journal de la Société des Américanistes. Tome 51, 1962. pp. 65-82

Towards a data-driven personalised management of Atopic Dermatitis severity

Atopic Dermatitis (AD, eczema) is a common inflammatory skin disease, characterised by dry and itchy skin. AD cannot be cured, but its long-term outcomes can be managed with treatments. Given the heterogeneity in patients' responses to treatment, designing personalised rather than ``one-size-fits-all" treatment strategies is of high clinical relevance. In this thesis, we aim to pave the way towards a data-driven personalised management of AD severity, whereby severity data would be collected automatically from photographs without the need for patients to visit a clinic, be used to predict the evolution of AD severity, and generate personalised treatment recommendations. First, we developed EczemaNet, a computer vision pipeline using convolution neural networks that detects areas of AD from photographs and then makes probabilistic assessments of AD severity. EczemaNet was internally validated with a medium-size dataset of images collected in a published clinical trial and demonstrated fair performance. Then, we developed models predicting the daily to weekly evolution of AD severity. We highlighted the challenges of extracting signals from noisy severity data, with small and practically not significant effects of environmental factors and biomarkers on prediction. We showed the importance of using high-quality measurements of validated and objective (vs subjective) severity scores. We also stressed the importance of modelling individual severity items rather than aggregate scores, and introduced EczemaPred, a principled approach to predict AD severity using Bayesian state-space models. Our models are flexible by design, interpretable and can quantify uncertainty in measurements, parameters and predictions. The models demonstrated good performance to predict the Patient-Oriented SCOring AD (PO-SCORAD). Finally, we generated personalised treatment recommendations using Bayesian decision analysis. We observed that treatment effects and recommendations could be confounded by the clinical phenotype of patients. We also pretrained our model using historical data and combined clinical and self-assessments. In conclusion, we have demonstrated the feasibility and the challenges of a data-driven personalised management of AD severity.Open Acces

Self-Consistent Velocity Matching of Probability Flows

We present a discretization-free scalable framework for solving a large class of mass-conserving partial differential equations (PDEs), including the time-dependent Fokker-Planck equation and the Wasserstein gradient flow. The main observation is that the time-varying velocity field of the PDE solution needs to be self-consistent: it must satisfy a fixed-point equation involving the probability flow characterized by the same velocity field. Instead of directly minimizing the residual of the fixed-point equation with neural parameterization, we use an iterative formulation with a biased gradient estimator that bypasses significant computational obstacles with strong empirical performance. Compared to existing approaches, our method does not suffer from temporal or spatial discretization, covers a wider range of PDEs, and scales to high dimensions. Experimentally, our method recovers analytical solutions accurately when they are available and achieves superior performance in high dimensions with less training time compared to alternatives

Automated Verification of Asynchronous Communicating Systems with TLA+

Verifying the compatibility of communicating peers is a crucial issue in critical distributed systems. Unlike the synchronous world, the asynchronous world covers a wide range of message ordering paradigms (e.g. FIFO or causal) that are instrumental to the compatibility of peer compositions. We propose a framework that takes into account the variety of asynchronous communication models and compatibility properties. The notions of peer, communication model, system and compatibility criteria are formalized in TLA+ to benefit from its verification tools. We present an implemented toolchain that generates TLA+ specifications from the behavioral descriptions of peers and checks compatibility of the composition with respect to given communication models and compatibility criteria

Courtage sémantique de services de calcul

La recherche du ou des services de calcul scientifique disponibles sur une grille qui répondent aux besoins d'un utilisateur, aussi appelée courtage de services, est une activité complexe. En effet, les services disponibles sont souvent conçus pour répondre de manière efficace à de nombreux besoins différents. Ceux-ci comportent donc en général de nombreux paramètres et la simple signature du service ne suffit pas pour que l'utilisateur puisse le trouver. La solution proposée dans ces travaux consiste à utiliser une description formelle du domaine d'application comportant l'ensemble des données et des opérateurs du domaine ainsi que les propriétés des opérateurs. Dans le cadre de cette thèse, cette description est effectuée sous la forme d'une spécification algébrique. Un service ou une requête sont alors des termes de l'algèbre associée. En ce qui concerne les signatures, nous combinons le sous-typage des sortes et la surcharge des opérateurs selon le système de type proposé par G. Castagna pour le λ&-calcul. Le courtage consiste alors à effectuer un filtrage modulo la théorie équationnelle associée à la spécification, entre le terme représentant le service souhaité et les termes représentant les services disponibles. Nous proposons et avons implanté deux algorithmes différents inspirés d'un parcours de l'arbre de recherche des solutions contraint par une quantité d'énergie (nombre d'équations et/ou de compositions applicables). Le premier algorithme est directement dérivé des travaux de Gallier et Snyder sur l'unification équationnelle. Nous avons montré sa correction et argumenté sa complétude (ou exhaustivité). Le second algorithme découle d'une définition constructive de l'ensemble des services qui peuvent répondre à la requête d'un utilisateur. L'algorithme consiste alors en un parcours particulier de l'arbre construit pour engendrer le service requis. Nous avons également montré sa correction, et sa complétude pour certaines formes d'équations. Nous illustrons notre approche dans les domaines applicatifs suivants : algèbre linéaire et optimisation, et nous nous intéressons au traitement de la combinaison de domaines applicatifs. ABSTRACT : The search for a computing service available on a grid which corresponds to an user's needs, also called trading services, is a complex activity. Indeed available services are often implemented to fulfill efficiently different requirements.These services offer many parameters and their signature is often not enough for a precise description. The object of this work consists in using a formal description of the dedicated domain : the data, the operators and their properties. This description is carried out as an algebraic specification. Services and requests are then terms of the associated algebra. For the signatures, we combine sub-sorting and overloading of operators by using the type system proposed by G. Castagna for the λ&-calculus. Trading is then implemented as an equational matching modulo the theory associated to the specification, between the term representing the required service and the terms representing the available services. We propose two algorithms inspired from a traversal of the solution search tree constrained by an amount of energy. The first one is directly inspired from the work of Gallier and Snyder on equational unification. We have proved its correctness and argued its completeness. The second one is derived from a constructive definition of the set of services which answer the user request. We have proved its correctness and its completeness for some kind of equations. We illustrate our approach with applications to linear algebra and optimization and an interaction between these two domains

Etude photo-aérienne des pâturages des hauts plateaux de l'Adamawa occidental

L'auteur a étudié, dans le cadre d'une thèse, les problèmes posés par la relation agriculture-élevage. Dans son ouvrage "La transformation du milieu physique sous l'effet du surpâturage sur les hauts plateaux de l'Adamawa", l'évolution des savanes est placée dans son cadre paléoclimatique et morphologique: érosion, effets du surpâturage sur la dynamique des cours d'eau. Il résume ici ses conclusions relatives à l'emploi de la photographie aérienne pour l'étude des pâturages. Les photographies utilisées ont été prises spécialement en vue de cette étude par le Service des activités aériennes de l'Institut géographique nationa

Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

Plug-and-Play (PnP) methods are efficient iterative algorithms for solving ill-posed image inverse problems. PnP methods are obtained by using deep Gaussian denoisers instead of the proximal operator or the gradient-descent step within proximal algorithms. Current PnP schemes rely on data-fidelity terms that have either Lipschitz gradients or closed-form proximal operators, which is not applicable to Poisson inverse problems. Based on the observation that the Gaussian noise is not the adequate noise model in this setting, we propose to generalize PnP using theBregman Proximal Gradient (BPG) method. BPG replaces the Euclidean distance with a Bregman divergence that can better capture the smoothness properties of the problem. We introduce the Bregman Score Denoiser specifically parametrized and trained for the new Bregman geometry and prove that it corresponds to the proximal operator of a nonconvex potential. We propose two PnP algorithms based on the Bregman Score Denoiser for solving Poisson inverse problems. Extending the convergence results of BPG in the nonconvex settings, we show that the proposed methods converge, targeting stationary points of an explicit global functional. Experimental evaluations conducted on various Poisson inverse problems validate the convergence results and showcase effective restoration performance

A relaxed proximal gradient descent algorithm for convergent plug-and-play with proximal denoiser

This paper presents a new convergent Plug-and-Play (PnP) algorithm. PnP methods are efficient iterative algorithms for solving image inverse problems formulated as the minimization of the sum of a data-fidelity term and a regularization term. PnP methods perform regularization by plugging a pre-trained denoiser in a proximal algorithm, such as Proximal Gradient Descent (PGD). To ensure convergence of PnP schemes, many works study specific parametrizations of deep denoisers. However, existing results require either unverifiable or suboptimal hypotheses on the denoiser, or assume restrictive conditions on the parameters of the inverse problem. Observing that these limitations can be due to the proximal algorithm in use, we study a relaxed version of the PGD algorithm for minimizing the sum of a convex function and a weakly convex one. When plugged with a relaxed proximal denoiser, we show that the proposed PnP-$\alpha$PGD algorithm converges for a wider range of regularization parameters, thus allowing more accurate image restoration