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stat.ML2025
Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations
Chengkun Li, Bobby Huggins, Petrus Mikkola +1
Bayesian inference with computationally expensive likelihood evaluations remains a significant challenge in many scientific domains. We propose normalizing flow regression (NFR), a…
stat.ML2021
Targeted Active Learning for Bayesian Decision-Making
Louis Filstroff, Iiris Sundin, Petrus Mikkola +3
Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way. However, maximizing the accu…
stat.ML2020
Projective Preferential Bayesian Optimization
Petrus Mikkola, Milica Todorović, Jari Järvi +2
Bayesian optimization is an effective method for finding extrema of a black-box function. We propose a new type of Bayesian optimization for learning user preferences in high-dimen…