Systematic Biology, Vol. 64, No. 1, SPECIAL ISSUE: MATHEMATICAL AND COMPUTATIONAL EVOLUTIONARY BIOLOGY (2013) (JANUARY 2015), pp. 66-83 (18 pages) Species tree methods are now widely used to infer the ...
This article considers causal inference for treatment contrasts from a randomized experiment using potential outcomes in a finite population setting. Adopting a Neymanian repeated sampling approach ...
This project demonstrates how to simulate and analyze neural tuning curve data using Bayesian inference via nested sampling. It combines theory, code, and visual intuition to explain how posterior ...
Abstract: Bayesian models and inference is a class of machine learning that is useful for solving problems where the amount of data is scarce and prior knowledge about the application allows you to ...
This code demonstrates how to perform Bayesian inference on a simple linear regression model using Gibbs sampling. The goal is to estimate the model parameters ...
Abstract: How to coordinate the design of sampling and Sparse-dense Matrix Multiplication (SpMM) is important in Graph Neural Network (GNN) acceleration. However, existing methods have an imbalance ...
Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Representative sampling and random sampling ...
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