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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 9 days ago
(Loreley, CEDAR and MAGELLAN). This project aims to design and develop an open-source management solution for a federated and distributed data exchange platform (DXP), operating in an open, scalable, and
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
Tong Zhang. Communication-efficient distributed optimization using an approximate newton-type method. In International conference on machine learning, pages 1000–1008. PMLR, 2014. [6] Lucas Theis, Wenzhe
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 18 days ago
, distinctiveness with respect to other landmarks, geometric accuracy and adequate distribution within the environment. To address these challenges, we propose to exploit the possibilities offered by MLLMs (e.g
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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systems Experience in deep learning, computer vision, or multimodal data integration Exposure to federated learning, privacy preserving analytics, or distributed systems Knowledge of clinical data models
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levels are constrained by a biogeochemical model (POLCOMS-ERSEM, Butenschön et al., 2016), whilst the benthos, cephalopods and fish are represented using species distribution models (Ben Rais Lasram et al
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, particularly in the context of signal estimation through filtering (Figure 1). This problem is particularly relevant for large-scale systems (e.g., energy distribution networks, sensor networks, gene regulation
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personnel. It is necessary to realize experience feedback on cases for which extinguishing, means were insufficient and find new indicators, notably biochemical, to better estimate the potential firepower in
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional
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time delays need to be compensated [6]. Accurate channel estimation is known to be a difficult task in UM-MIMO settings [7,8] as it usually relies only on pilot symbols to estimate a large number of