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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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theory, statistical inference, and probabilistic modelling for uncertainty quantification in deep learning, particularly large language models. The focus will be on quantifying and evaluating uncertainty
Searches related to bayesian inference
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