4 papers · 1 filter
LoBoost: Fast Model-Native Local Conformal Prediction for Gradient-Boosted Trees
Vagner Santos, Victor Coscrato, Luben Cabezas +2
Gradient-boosted decision trees are among the strongest off-the-shelf predictors for tabular regression, but point predictions alone do not quantify uncertainty. Conformal predicti…
Trustworthy scientific inference with generative models
James Carzon, Luca Masserano, Joshua D. Ingram +7
Generative artificial intelligence (AI) excels at producing complex data structures (text, images, videos) by learning patterns from training examples. Across scientific discipline…
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference
Niccolò Dalmasso, Luca Masserano, David Zhao +2
Many areas of science rely on simulators that implicitly encode intractable likelihood functions of complex systems. Classical statistical methods are poorly suited for these so-ca…
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
Luca Masserano, Alex Shen, Michele Doro +3
An open scientific challenge is how to classify events with reliable measures of uncertainty, when we have a mechanistic model of the data-generating process but the distribution o…