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queries within embedded knowledge graphs. It will involve designing or adapting efficient indexing structures tailored for vector databases and exploring hybrid neurosymbolic techniques to enhance query
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[2, 4, 5]; - Lack of common representation for process flowsheets (graph incidence matrix, custom-made dedicated language, SFILES 2.0 standard) - Various custom-made process simulation environments
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. - Compilation of a curated catalog of archaeal genomes from public data and newly obtained data within the team. - Orthogroup inference, multi-clade pangenome graphs to detect genes with restricted distributions
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of convolutional neural networks, graph neural networks, and attention-based architectures, with the attention mechanisms explicitly guided by the physical principles and intrinsic properties of the atmosphere
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carried out within the Theory team of the Solid State Physics Laboratory (CNRS-UMR 8502). This research project receives funding from the French National Research Agency (ANR). Self-assembly