🏢 University of Helsinki

Eliciting high-dimensional probability distributions from experts using only preference comparisons is achieved via normalizing flows and a novel functional prior, resolving the problem of collapsing …

Meta-learning and differential privacy combine to enable accurate, well-calibrated private regression, even with limited data, via the novel DPConvCNP model.