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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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Rennes (Brittany) Surface viscosity is a fundamental property of fluid interfaces: it quantifies their resistance to deformation and controls many physical and industrial processes. It plays a key role in
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Traitement du Signal et des Images, 2023. Douté, S., Forbes, F., Borkowski, S., Meyer, L., Heidmann, S., 2024. Massive analysis of multi-angular images by inverse regression of reflectance models
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a joint research unit (University of Rennes and CNRS) with 150 staff, including 60 researchers and lecturers, specialising in the study of geological and environmental processes. Keywords: Optically
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of expensive evaluations required for prediction and optimization. A classical approach is co-Kriging (Kennedy--O'Hagan), which models the high-fidelity response through an autoregressive Gaussian process (GP
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
science as part of the ERC Starting Grant project Incorwave, which aims to develop advanced numerical and mathematical methods for passive seismic imaging. The research will focus on two key-directions: (1
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other labs will be developed for comparison with other techniques and computer IRIS Lab for analyses of the 3D mapping by IA models References [1] A. Kiełbasa, K. Kowalczyk, K. Chajec-Gierczak, J. Bała
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lining of blood vessels— which plays a central role in the development of vascular diseases. Blood vessels further complicate this picture through their complex geometries, featuring diameter variations
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation