MCMC sample analysis, kernel densities, plotting, and GUI

kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order

Kernel Density Estimation and (re)sampling

Kernel density estimation on a sphere

Random Forests for Density Estimation in Python

Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image Enhancement, CVPRW 2024. Best LPIPS in NTIRE chanllenge.

Kernel density estimation via diffusion in 1d and 2d.

Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published at NeurIPS 2022.

KEN: Unleash the power of large language models with the easiest and universal non-parametric pruning algorithm

Improving the feature density based peak caller with dynamic statistics

Lightning fast, lightweight, and reliable kernel density estimation for 1d and 2d samples

Kernel density integral transformation: feature preprocessing and univariate clustering (TMLR, 2023)

Weighted and iterative KDE to improve outlier detection

Using kernel density estimation to detect outliers in California's medicare data

MultiVariate Gaussian Kernel Density Estimation

Kernel-based Design of Experiments

Code for the paper "An Empirical Analysis of KDE-based Generative Models on Small Datasets"

Non parametric Kernel Density Estimator / Classifier. Allows user to input bandwidth but does not find it. Can classify for N dimensions, but can only plot class / decision boundaries for 2.

Fast univariate kernel density estimation with the polynomial-exponential kernel