Memory efficient seismic inversion via trace estimation

Memory efficient convolution networks

A dataset bucket with a machine learning bias auditor. Built with Python-Flask, MaterializeCSS and the Kaggle API.

This repository provides configuration for highly accurate and unbiased responses from Chat-GPT

Calculate the standard deviation of a strided array using Welford's algorithm.

Calculate the variance of a strided array ignoring NaN values and using Welford's algorithm.

Compute a sample Pearson product-moment correlation matrix incrementally.

Compute a variance-to-mean ratio (VMR) incrementally.

Calculate the variance of a strided array using a one-pass textbook algorithm.

Calculate the variance of a single-precision floating-point strided array.

Calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.

Calculate the mean and variance of a double-precision floating-point strided array.

Compute an arithmetic mean and unbiased sample variance incrementally.

Calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm.

Calculate the variance of a double-precision floating-point strided array using Welford's algorithm.

Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass trial mean algorithm.

Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.

Calculate the standard deviation of a strided array using a two-pass algorithm.

Calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.

Calculate the variance of a strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.