doing audio digital signal processing in tensorflow to try to recreate digital audio effects

Python implementation of Levenberg-Marquardt algorithm built from scratch using NumPy.

GPU/TPU accelerated nonlinear least-squares curve fitting using JAX

MITx 6.86x | Machine Learning with Python | From Linear Models to Deep Learning

Benchmark a given function for variable input sizes and find out its time complexity

Nonlinear Regression for Agricultural Applications

Fitting dose-response models in R

Robust Gaussian Process with Iterative Trimming

Nonlinear regression in Julia

Easy to use high level python library for popular machine learning algorithms. Has in-built support for graphing and optimizers based in C++.

Robust Regression for arbitrary non-linear functions

{gslnls}: GSL multi-start nonlinear least-squares fitting in R

Hierarchical dose-response models in R

GMPE-estimation implements a one-stage estimation algorithm to estimate ground-motion prediction equations (GMPE) with spatial correlation. It also quantifies the uncertainty of spatial correlation and intensity measure predictions.

This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/

Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)

Neural nets for high accuracy multivariable nonlinear regression.

one day introduction to generalized nonlinear models using the gnm and logmult R packages

a c++ library with statistical machine learning algorithms for linear and non-linear robust regression that can be used with python.

An R package for seed germination assays