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kernel-ridge-regression

Here are 33 public repositories matching this topic...

elcorto / pwtools

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.

python sqlite molecular-dynamics lammps preprocessing quantum-espresso polynomial-regression cp2k multivariate-regression radial-basis-function kernel-regression postprocessing radial-distribution-function ase parameter-sweep kernel-ridge-regression quasi-harmonic-approximation cpmd radial-pair-correlation-function

Updated Aug 28, 2023
Python

binghuang2018 / aqml

Amons-based quantum machine learning for quantum chemistry

machine-learning cheminformatics quantum-chemistry active-learning kernel-ridge-regression training-set-selection multi-fidelity-krr molecular-representation

Updated Jun 7, 2022
Python

mlatom

dralgroup / mlatom

AI-enhanced computational chemistry

machine-learning deep-learning neural-network quantum-mechanics artificial-intelligence computational-chemistry quantum-chemistry quantum-chemistry-programs kernel-ridge-regression kernel-method machine-learning-potential

Updated May 8, 2024
Python

Kennethborup / self_distillation

Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression

self-training resnet ridge-regression knowledge-distillation distillation kernel-ridge-regression self-distillation

Updated Oct 12, 2021
Jupyter Notebook

MLQD

Arif-PhyChem / MLQD

MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics

python machine-learning artificial-intelligence convolutional-neural-networks kernel-ridge-regression quantum-dynamics open-quantum-systems krr quantum-dissipative-dynamics spin-boson-model fmo-complex aiqd ostl mlqd

Updated Nov 17, 2023
Jupyter Notebook

qin-yu / julia-regression-boston-housing

2018 [Julia v1.0] machine learning (linear regression & kernel-ridge regression) examples on the Boston housing dataset

machine-learning julia linear-regression regression supervised-learning introduction boston-housing-price-prediction boston-housing boston-housing-dataset kernel-ridge-regression

Updated Dec 13, 2018
Julia

lsorber / neo-ls-svm

Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation

python machine-learning kernel-methods support-vector-machines gaussian-processes kernel-ridge-regression conformal-prediction prediction-intervals ls-svm

Updated Apr 1, 2024
Python

Machine-Learning-in-Molecular-Sciences

nickcafferry / Machine-Learning-in-Molecular-Sciences

2017 Summer School on the Machine Learning in the Molecular Sciences. This project aims to help you understand some basic machine learning models including neural network optimization plan, random forest, parameter learning, incremental learning paradigm, clustering and decision tree, etc. based on kernel regression and dimensionality reduction,…

machine-learning random-forest clustering feature-selection dimensionality-reduction artificial-neural-networks gaussian-processes learning-curve kernel-ridge-regression delta-learning-rule parameter-learning

Updated May 16, 2022
Jupyter Notebook

AmishaSomaiya / Machine-Learning

Machine Learning Code Implementations in Python

numpy rbf-kernel pytorch neural-networks mnist-classification representation-learning principal-component-analysis kmeans-clustering lasso-regression central-limit-theorem kmeans-clustering-algorithm kernel-ridge-regression polynomial-kernel self-supervised-learning regularized-logistic-regression coordinate-descent-algorithm native-python simclr lloyds-algorithm vision-representations

Updated May 9, 2024
Python

sudeshnapal12 / Machine-Learning-algorithms-Matlab

Contains ML Algorithms implemented as part of CSE 512 - Machine Learning class taken by Fransico Orabona. Implemented Linear Regression using polynomial basis functions, Perceptron, Ridge Regression, SVM Primal, Kernel Ridge Regression, Kernel SVM, Kmeans.

svm perceptron kmeans ridge-regression kernel-svm kernel-ridge-regression

Updated Dec 17, 2017
TeX

superlj666 / Distributed-Learning-with-Random-Features

Codes and experiments for paper "Distributed Learning with Random Features". Preprint.

kernel-ridge-regression random-features devide-and-conquer

Updated Mar 18, 2020
MATLAB

Quantum_dissipative_dynamics_with_kernel_methods

Arif-PhyChem / Quantum_dissipative_dynamics_with_kernel_methods

Speeding up quantum dissipative dynamics of open systems with kernel methods

python machine-learning artificial-intelligence kernel-ridge-regression quantum-dynamics open-quantum-systems krr spin-boson-model mlatom

Updated Mar 2, 2022
Shell

windhaunting / kernel_methods

kernel linear regression and svm for Creditcard and Tumor data

svm kernel-ridge-regression

Updated Nov 7, 2017
Python

jakublala / alchemical-kernels

Pytorch implementation of Alchemical Kernels from Phys. Chem. Chem. Phys., 2018,20, 29661-29668

soap kernel-ridge-regression energy-prediction alchemical-kernel rascaline elpasolite

Updated Aug 11, 2022
Python

elcorto / gp_playground

Explore selected topics related to Gaussian processes

machine-learning scikit-learn gaussian-processes kernel-ridge-regression gpytorch gpy tinygp

Updated Jun 20, 2023
Python

tjarkpr / learning-soft-computing-fhwedel

Lecture "Learning & soft computing" @fh-wedel SS22

nlp sarcasm-detection kernel-ridge-regression fh-wedel

Updated Jul 7, 2022
Jupyter Notebook

charumakhijani / advanced-house-price-prediction

exploratory-data-analysis data-visualization kaggle-competition outlier-detection scaling house-price-prediction lasso-regression support-vector-regression kfold-cross-validation ensemble-models kernel-ridge-regression random-forest-regression missing-value-treatment skewed-data one-hot-encoding xgbregressor elastic-net-regression rmse-score lgbmregressor gradient-boosting-regression

Updated Sep 30, 2020
Jupyter Notebook

butler-julie / SRE

Sequential Regression Extrapolation (SRE): An accurate method of extrapolation using machine learning

machine-learning linear-regression machine-learning-algorithms machinelearning ridge-regression kernel-regression extrapolation regression-algorithms kernel-ridge-regression

Updated May 13, 2021
Jupyter Notebook

lukebella / SpotifyRegression

Implementation of (Kernel) Ridge Regression predictors from scratch on Kaggle's Spotify Tracks Dataset.

python machine-learning kaggle ridge-regression kernel-ridge-regression nested-cross-validation

Updated Nov 26, 2023
Jupyter Notebook

anupriya1519 / Machine-Learning

Assignments

svm heatmap ridge-regression kernel-ridge-regression svm-polynomial-kernel svm-rbf

Updated Mar 20, 2018
Jupyter Notebook

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