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Modern statistical analyses often involve testing large numbers of hypotheses. In many situations, these hypotheses may have an underlying tree structure that not only helps determine the order that tests should be conducted but also…

Methodology · Statistics 2019-03-19 Yunxiao Li , Yi-Juan Hu , Glen A. Satten

A framework for the mathematical modeling of evolution in group structured populations is introduced. The population is divided into a fixed large number of groups of fixed size. From generation to generation, new groups are formed that…

Populations and Evolution · Quantitative Biology 2011-06-24 Roberto H. Schonmann , Renato Vicente , Nestor Caticha

It is important to understand how protein folding and evolution influences each other. Several studies based on entropy calculation correlating experimental measurement of residue participation in folding nucleus and sequence conservation…

Biomolecules · Quantitative Biology 2007-05-23 Yan Yuan Tseng , Jie Liang

Hypothesis testing of structure in covariance matrices is of significant importance, but faces great challenges in high-dimensional settings. Although consistent frequentist one-sample covariance tests have been proposed, there is a lack of…

Methodology · Statistics 2020-07-22 Kyoungjae Lee , Lizhen Lin , David Dunson

The software program BAMM has been widely used to study the dynamics of speciation, extinction, and phenotypic evolution on phylogenetic trees. The program implements a model-based clustering algorithm to identify clades that share common…

Quantitative Methods · Quantitative Biology 2017-11-10 Daniel L Rabosky

Dynamic fault trees (DFTs) have emerged as an important tool for capturing the dynamic behavior of system failure. These DFTs are then analyzed qualitatively and quantitatively using stochastic or algebraic methods to judge the failure…

Logic in Computer Science · Computer Science 2017-12-11 Yassmeen Elderhalli , Osman Hasan , Waqar Ahmad , Sofiene Tahar

Conformal field theories (CFTs) feature prominently in high-energy physics, statistical mechanics, and condensed matter. For example, CFTs govern emergent universal properties of systems tuned to quantum phase transitions, including their…

We present a new method for counterfactual explanations (CFEs) based on Bayesian optimisation that applies to both classification and regression models. Our method is a globally convergent search algorithm with support for arbitrary…

Machine Learning · Computer Science 2021-06-30 Thomas Spooner , Danial Dervovic , Jason Long , Jon Shepard , Jiahao Chen , Daniele Magazzeni

A simple analytical framework to study the molecular quasispecies evolution of finite populations is proposed, in which the population is assumed to be a random combination of the constiyuent molecules in each generation,i.e., linkage…

Statistical Mechanics · Physics 2016-08-31 Domingos Alves , J. F. Fontanari

Structure discovery in graphical models is the determination of the topology of a graph that encodes conditional independence properties of the joint distribution of all variables in the model. For some class of probability distributions,…

Machine Learning · Statistics 2016-04-07 Wacha Bounliphone , Matthew Blaschko

We propose a simple single-step multiple testing procedure that asymptotically controls the family-wise error rate (FWER) at the desired level exactly under the equicorrelated multivariate Gaussian setup. The method is shown to be…

Statistics Theory · Mathematics 2025-08-14 Swarnadeep Datta , Monitirtha Dey

Feature screening for ultrahigh-dimension, in general, proceeds with two essential steps. The first step is measuring and ranking the marginal dependence between response and covariates, and the second is determining the threshold. We…

Methodology · Statistics 2022-07-28 Linsui Deng , Yilin Zhang

Correlated observations are ubiquitous phenomena in a plethora of scientific avenues. Tackling this dependence among test statistics has been one of the pertinent problems in simultaneous inference. However, very little literature exists…

Statistics Theory · Mathematics 2024-11-20 Monitirtha Dey

Effective Field Theory (EFT) is a general framework to parametrize the low-energy approximation to a UV model that is widely used in model-independent searches for new physics. The use of EFTs at the LHC can suffer from a 'validity' issue,…

High Energy Physics - Phenomenology · Physics 2026-02-03 Spencer Chang , Markus A. Luty , Teng Ma , Francesco Montagno , Andrea Wulzer

Reaction-diffusion models are often used to describe biological invasion, where populations of individuals that undergo random motility and proliferation lead to moving fronts. Many models of biological invasion are extensions of the…

Populations and Evolution · Quantitative Biology 2024-01-09 Matthew J Simpson , Nizhum Rahman , Alexander KY Tam

We study classifiers operating under severe classification time constraints, corresponding to 1-1000 CPU microseconds, using Convolutional Tables Ensemble (CTE), an inherently fast architecture for object category recognition. The…

Computer Vision and Pattern Recognition · Computer Science 2016-02-16 Aharon Bar-Hillel , Eyal Krupka , Noam Bloom

Mutation testing has emerged as a powerful technique for evaluating the effectiveness of test suites for Deep Neural Networks. Among existing approaches, the statistical mutant killing criterion of DeepCrime has leveraged statistical…

Software Engineering · Computer Science 2025-07-16 Jinhan Kim , Nargiz Humbatova , Gunel Jahangirova , Shin Yoo , Paolo Tonella

Multi-gene panel testing allows efficient detection of pathogenic variants in cancer susceptibility genes including moderate-risk genes such as ATM and PALB2. A growing number of studies examine the risk of breast cancer (BC) conferred by…

This paper describes an Artificial Embryology method (called ``Epigenetic Tracking'') to generate predefined arbitrarily shaped 2-dimensional arrays of cells by means of evolutionary techniques. It is based on a model of development, whose…

Adaptation and Self-Organizing Systems · Physics 2008-05-19 Alessandro Fontana

Reproducibility is a fundamental requirement for validating scientific claims in computational research. Stochastic computational models are widely used in fields such as systems biology, financial modeling and environmental sciences.…