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multiple tensor modeling: Several data modalities, including invasive (intracardiac electrograms, electroanatomic maps) and noninvasive (ECG, echocardiography), are acquired in the management of persistent
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on baseline patients’ profile. Finally, we aim at enriching spatio-temporal treatment response models accounting for multiple imaging modalities (PET – CT) along with clinical and biological informations
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for multiple imaging modalities (PET – CT) along with clinical and biological informations. Typical data-driven approaches are characterized by lack of interpretability and scalability problems, due
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- Benchmarking model-based and learning-based techniques for LiDAR-camera fusion - Designing new LiDAR-Camera fusion method that focus on the accurate and dense alignment of the two modalities - Adapting
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, as well as the development of age-related pathologies, including cancer. IRCAN has access to multiple platforms covering various aspects of molecular and cellular biology, as well as the use of model
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Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
multiple functions (e.g. thermal, barrier and couplings…) and thus the properties of use. Representation and digital mechanics tools will be used to solve the various digital cases. The project could draw
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the value of each client's dataset [20-22]. These issues are highly relevant in the developing data economy where multiple online data exchange platforms, such as AWS data exchange [23] and Dawex [24
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experimental data and is testable across multiple unlearning scenarios. For this we plan to apply for the first time Spiking Neural Networks (SNNs) to the modeling of unlearning. SNNs have recently shown