Background In high-throughput studies, hundreds to millions of hypotheses are typically
tested. Statistical methods that control the false discovery rate (FDR) have emerged as …

Scientists from nearly all disciplines face the problem of simultaneously evaluating many
hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible …

In multiple-testing problems, where a large number of hypotheses are tested simultaneously,
false discovery rate (FDR) control can be achieved with the well-known Benjamini …

Adaptive novelty detection with false discovery rate guarantee Page 1 The Annals of Statistics
2024, Vol. 52, No. 1, 157–183 https://doi.org/10.1214/23-AOS2338 © Institute of Mathematical …

Conditional calibration for false discovery rate control under dependence Page 1 The Annals of
Statistics 2022, Vol. 50, No. 6, 3091–3118 https://doi.org/10.1214/21-AOS2137 © Institute of …

This paper presents a conformal inference method for out-of-distribution testing that
leverages side information from labelled outliers, which are commonly underutilized or even …

This paper develops novel conformal methods to test whether a new observation was
sampled from the same distribution as a reference set. Blending inductive and transductive …

High-throughput biological data analysis commonly involves identifying features such as
genes, genomic regions, and proteins, whose values differ between two conditions, from …

Introduction Despite an impressive amount of metabolomics studies in animal models and
humans, most findings have not yet translated into the clinical setting, and the road ahead …

The aim is to detect novelties, namely Xis with Pi= P0. This task is illustrated in Figure 1 on a
classical image data set, where we want to detect hand-written digit '9's in the test sample …