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within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR modelling
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working within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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for approximate inference, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. It comprises Jan-Willem van de Meent, who
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, 2022) and extended this to the triple equivalence between neural dynamics, Bayesian inference, and algorithmic computation (Commun Phys, 2025). -We validated it within in vitro neural networks (Nature
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algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies during transport, and to develop statistical thresholds that balance detection
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circuit mechanism underlying higher cognitive functions such as multitasking, rule-based reasoning and Bayesian inference). In addition to the above areas, there is extensive expertise available in
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Location: Ithaca, New York 14850, United States of America [map ] Subject Areas: Data Science / Statistics , Applied Mathematics , Artificial Intelligence , Bayesian Statistics , Big Data , Scientific
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, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. It comprises Jan-Willem van de Meent, who serves as director, Max
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 2 months ago
specifically, we use simulation-based inference (SBI) [1], a Bayesian approach that leverages deep generative models, such as conditional normalizing flows and score-diffusion models, to approximate