#Gaussian-processes
Showing 24 of 24 repositories tagged #gaussian-processes, ranked by stars
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Machine learning, in numpy
A Python implementation of global optimization with gaussian processes.
Notebooks about Bayesian methods for machine learning
Gaussian processes in TensorFlow
Tree-Boosting, Gaussian Processes, and Mixed-Effects Models
Gaussian processes in JAX and Equinox.
Parallel Hyperparameter Tuning in Python
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
A Visual Exploration of Gaussian Processes
Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
Python library for Bayesian hyper-parameters optimization
Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
Deep convolutional gaussian processes.
Max-value Entropy Search for Efficient Bayesian Optimization
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).
Learning for Task and Motion Planning (LTAMP)
Python library to implement advanced trading strategies using machine learning and perform backtesting.
Homemade GP codes for easy DIY and study
Forecasting Netflix Customer Retention based on Gaussian Process Regression