Anisotropic smoothing for change-point regression data
-
Updated
May 21, 2024 - Roff
Anisotropic smoothing for change-point regression data
This is the recent work of my on the importance and application of mathematical function around its Hilbert function theory on artificial intelligence algorithms. The main motivation was the desire of improving the convergence rate and learning rate of various learning algorithms via Generalized Gaussian Radial Basis Function.
Tool for non-parametric curve fitting using local polynomials.
pwtools is a Python package for pre- and postprocessing of atomistic calculations, mostly targeted to Quantum Espresso, CPMD, CP2K and LAMMPS. It is almost, but not quite, entirely unlike ASE, with some tools extending numpy/scipy. It has a set of powerful parsers and data types for storing calculation data.
Train a neural network in feature and lazy regimes on a regression task defined on the hyper-sphere.
My realization of kernel regression.
Nonparametric regression examples with R and Python
This R package repository performs optimal transport and kernel regression hypothesis testing. Functions to perform large scale simulations are also provided.
This repo contains an R package to execute ROKET's real data analysis workflow on TCGA cancer types
Implementation of a Gaussian Kernel Regression for Temperature prediction using PySpark.
Calibration of an air pollution sensor monitoring network in uncontrolled environments with multiple machine learning algorithms
Identifying the most influential food groups on COVID-19 recovery rate: exploratory data analysis and statistical modeling
Sequential Regression Extrapolation (SRE): An accurate method of extrapolation using machine learning
Implementation of various Machine Learning Algorithms and Machine Learning Concepts in Python
Machine-Learning-Regression
For quick search
Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)
Guide for the Baccarelli Lab GitHub
Shared Bike Volumn Prediction
Add a description, image, and links to the kernel-regression topic page so that developers can more easily learn about it.
To associate your repository with the kernel-regression topic, visit your repo's landing page and select "manage topics."