Understanding Homoskedasticity in Regression Modeling With Examples

Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.
C&EN

Validation Challenge of Density-Functional Theory for Peptides—Example of Ac-Phe-Ala

‡ Physical and Theoretical Chemistry Laboratory, University of Oxford, OX1 3QZ Oxford, U.K. § Department of Mechanical Engineering and Materials Science and Center for Materials Genomics, Duke ...
IEEE

Bayesian learning of probability density functions: A Markov chain Monte Carlo approach

Abstract: The paper considers the problem of reconstructing a probability density function from a finite set of samples independently drawn from it.We cast the problem in a Bayesian setting where the ...
IEEE

A Kernel Density Estimation Based Loss Function and its Application to ASV-Spoofing Detection

Abstract: Biometric systems are exposed to spoofing attacks which may compromise their security, and voice biometrics, also known as automatic speaker verification (ASV), is no exception. Replay, ...