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Graduation: Progressive Relational Data Augmentation
Position type : IA, IHM, Science des Données
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Showing results 1 to 12 of 12 in total
Stage : 1 to 12 of 12 in total
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Modélisation automatique des variations phonétiques en français et en japonais : une approche comparative par apprentissage automatique
Position type : IA, Sciences et Technologies des langues
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Neural Architecture Growthfor Frugal Learning
Position type : IA, Science des Données
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Relevance and conspicuousness of facial information conveyed in videoconferencing systems
Position type : IHM
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LAPLACE – Learning poorly known and observed large scale systems
Position type : MécaFlu, Science des Données
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Benchmarking Parameter-Efficient Fine-tuning methodsfor Spoken Language Understanding task
Position type : Sciences et Technologies des langues
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Physics-aware Representation Learning for Turbulent Dynamo Data (leading to a potential PhD position within the project)
Position type : MécaFlu
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