Using Quantum Speed-Ups to accelerate Gaussian Process Regression
-
Updated
Jul 9, 2024 - Python
Using Quantum Speed-Ups to accelerate Gaussian Process Regression
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
Example machine learning applications for the determination of the residual yield force of corroded steel bars tested under monotonic tensile loading. Data is collected from 26 experimental programs avaialbe in the literature.
Code used to predict hydrogen atom transfer (HAT) energy barriers using Gaussian Process Regression
Gaussian Process Regression vs. Relevance Vector Machine.
Stochastic Process Library for Python
Minimal Implementation of Bayesian Optimization in JAX
A Neural Network that predicts the direction of a force experienced by the Syntouch Biotac robotic finger
Surrogate Final BH properties
Project for the Data Science PhD course of Probability
Code for "Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties"
Hierarchical Gaussian Processes based Multi-Robot Relative Localization
Engineering Thesis written to predict fault detection in wind turbines using Python
Estimation of the Hubble constant using Gaussian process regression and viable alternatives
Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression
Official implementation of Self-Distillation for Gaussian Processes
Study of Gaussian Process (GP) local and global approximations, and application of the sparse GP approximation, combining both the global and local approaches.
Gaussian process regression-based adversarial image detection
Modelling stellar activity signals with Gaussian process regression networks
卒業研究の実験のために書いたソースコードです。全てのコードを1から書きました。(自動生成されたコードであるcython_wl_kernel.cppを除く)
Add a description, image, and links to the gaussian-process-regression topic page so that developers can more easily learn about it.
To associate your repository with the gaussian-process-regression topic, visit your repo's landing page and select "manage topics."