[IJCAI 2025] Optimized View and Geometry Distillation from Multi-view Diffuser

Memory efficient seismic inversion via trace estimation

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

Memory efficient convolution networks

A type theory for unbiased cartesian closed categories.

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

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.

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

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

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

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

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

Calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.

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

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

Calculate the standard deviation of a strided array.

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