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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 3 hours ago
repeated over several trials (to collect multiple samples) before making a decision. For these applications, statistical methods for hypothesis testing and estimation are needed, with formal guarantees
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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. We will develop a posteriori estimation tools to obtain error indicators that will guide mesh adaptation. These indicators must be specifically designed to account for the anisotropy of the field. Our
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evolutionary). The project aims to approximate a Boltzmann distribution associated with an objective function that is difficult to optimize in order to solve complex optimization problems. This probabilistic
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 4 days ago
. The project will initially focus on the Grenoble metropolitan area, with the objective of developing methods that are scalable and transferable to other regions at the international level. This position is part
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hundreds of hours of exposure) in order to estimate systematic errors. - Develop open-source analysis pipelines for extracting diffuse emission from objects with very low surface brightness. Take into
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., 2024). In a wider context, crack detection has received a lot of attention and, since some preliminary attempts such as DeepCrack (Liu et al., 2019), numerous methods using deep learning have been
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. In particular, he/she will be expected to :• Select and evaluate the most suitable approaches from the wide range of machine learning and computer vision methods available in the literature, with
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
space for flower petals, while not being applicable to growing flowers. Existing methods to reconstruct growing flower petals from vision sensors fit a pre-defined template to observations [2
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computer scientists (U1331 Unit page ). The Cavalli Lab (located at Institut Curie St-Cloud, west of Paris), investigates tumor heterogeneity, targeting clinically relevant questions. The goal of our