Robust robotic localization and mapping, together with NavAbility(TM). Reach out to info@wherewhen.ai for help.

A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.

Multivariate Local Polynomial Regression and Radial Basis Function Regression

JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python

Python code for calculating non-parametric morphological diagnostics of galaxy images.

A data-driven approach for interactively synthesizing diverse images from semantic label maps.

Parametric and non-parametric statistical tests

Repo containing code for Towards Data Science articles

An R package for kernel density estimation with parametric starts and asymmetric kernels.

This code belongs to ACL conference paper entitled as "An Online Semantic-enhanced Dirichlet Model for Short Text Stream Clustering"

📘 This repository offers a complete K-Nearest Neighbors (KNN) tutorial, guiding you from core theory to hands-on practice. Learn to implement KNN from scratch with NumPy, apply it using scikit-learn, and explore visualizations, datasets, and Jupyter notebooks to fully understand, test, and optimize the algorithm.

An algorithm that decimates a curve composed of line segments to a similar curve with fewer points.

Non-parametric method for estimating regime change in bivariate time series setting.

Python module for computing Symbolic Mutual Information and symbolic Transfer of Entropy

A 30+ node flowchart for selecting the right statistical test for evaluating experimental data.

This is the R code for several common non-parametric methods (kernel est., mean regression, quantile regression, boostraps) with both practical applications on data and simulations

UAP-BEV: Uncertainty Aware Planning in Bird's Eye View Generated from Monocular Images (CASE' 23)

Generalized Pairwise Comparisons

Tool for non-parametric curve fitting using local polynomials.

NORTA.jl implements the Normal to Anything (NORTA) concept, leveraging Julia's framework to provide a unique approach that utilizes non-parametric distribution fitting methods, thereby enhancing efficiency by eliminating the need for explicit correlation matrix computations.