5 citations · 9 across the 11 of their papers we have counts for
11 papers
Tabular foundation models for the estimation of probabilistic quasar photometric redshifts in S-PLUS
Raquel R. Valença, Lilianne Nakazono, Rafael Izbicki +6
We assess whether tabular foundation models can be used as off-the-shelf probabilistic photometric-redshift estimators for quasars in the 12-band S-PLUS DR6 survey, where colour-re…
Benchmarking Tabular Foundation Models for Conditional Density Estimation in Regression
Rafael Izbicki, Pedro L. C. Rodrigues
Conditional density estimation (CDE) - recovering the full conditional distribution of a response given tabular covariates - is essential in settings with heteroscedasticity, multi…
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…
DiNo and RanBu: Lightweight Predictions from Shallow Random Forests
Tiago Mendonça dos Santos, Rafael Izbicki, Luís Gustavo Esteves
Random Forest ensembles are a strong baseline for tabular prediction tasks, but their reliance on hundreds of deep trees often results in high inference latency and memory demands,…
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…
On Focusing Statistical Power for Searches and Measurements in Particle Physics
James Carzon, Aishik Ghosh, Rafael Izbicki +3
Particle physics experiments rely on the (generalised) likelihood ratio test (LRT) for searches and measurements, which consist of composite hypothesis tests. However, this test is…
On the Utility Function of Experiments in Fundamental Science
Tommaso Dorigo, Michele Doro, Max Aehle +7
The majority of experiments in fundamental science today are designed to be multi-purpose: their aim is not simply to measure a single physical quantity or process, but rather to e…
The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts
L. Nakazono, R. R. Valença, G. Soares +12
The advent of massive broad-band photometric surveys enabled photometric redshift estimates for unprecedented numbers of galaxies and quasars. These estimates can be improved using…
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…
Toward the End-To-End Optimization of the SWGO Array Layout
Tommaso Dorigo, Max Aehle, Cornelia Arcaro +13
In this document we consider the problem of finding the optimal layout for the array of water Cherenkov detectors proposed by the SWGO collaboration to study very-high-energy gamma…
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…