gpDifferentiable Gaussian Process implementation for PyTorch
Stars: ✭ 18 (-43.75%)
ml course"Learning Machine Learning" Course, Bogotá, Colombia 2019 #LML2019
Stars: ✭ 22 (-31.25%)
DynamlScala Library/REPL for Machine Learning Research
Stars: ✭ 195 (+509.38%)
PysotSurrogate Optimization Toolbox for Python
Stars: ✭ 136 (+325%)
PilcoBayesian Reinforcement Learning in Tensorflow
Stars: ✭ 222 (+593.75%)
CeleriteScalable 1D Gaussian Processes in C++, Python, and Julia
Stars: ✭ 155 (+384.38%)
Stheno.jlProbabilistic Programming with Gaussian processes in Julia
Stars: ✭ 318 (+893.75%)
approxposteriorA Python package for approximate Bayesian inference and optimization using Gaussian processes
Stars: ✭ 36 (+12.5%)
NasbotNeural Architecture Search with Bayesian Optimisation and Optimal Transport
Stars: ✭ 120 (+275%)
GpstuffGPstuff - Gaussian process models for Bayesian analysis
Stars: ✭ 106 (+231.25%)
Bayesian OptimizationPython code for bayesian optimization using Gaussian processes
Stars: ✭ 245 (+665.63%)
brunoa deep recurrent model for exchangeable data
Stars: ✭ 34 (+6.25%)
GpytorchA highly efficient and modular implementation of Gaussian Processes in PyTorch
Stars: ✭ 2,622 (+8093.75%)
lgprR-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.
Stars: ✭ 22 (-31.25%)
BtbA simple, extensible library for developing AutoML systems
Stars: ✭ 159 (+396.88%)
GPJaxA didactic Gaussian process package for researchers in Jax.
Stars: ✭ 159 (+396.88%)
Safe learningSafe reinforcement learning with stability guarantees
Stars: ✭ 140 (+337.5%)
bayexBayesian Optimization in JAX
Stars: ✭ 24 (-25%)
VbmcVariational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
Stars: ✭ 123 (+284.38%)
ExoplanetFast & scalable MCMC for all your exoplanet needs!
Stars: ✭ 122 (+281.25%)
BcpdBayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
Stars: ✭ 116 (+262.5%)
Universal Head 3DMMThis is a Project Page of 'Towards a complete 3D morphable model of the human head'
Stars: ✭ 138 (+331.25%)
pyrffpyrff: Python implementation of random fourier feature approximations for gaussian processes
Stars: ✭ 24 (-25%)
SafeoptSafe Bayesian Optimization
Stars: ✭ 90 (+181.25%)
Good PapersI 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
Stars: ✭ 248 (+675%)
random-fourier-featuresImplementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
Stars: ✭ 50 (+56.25%)
Stheno.jlProbabilistic Programming with Gaussian processes in Julia
Stars: ✭ 233 (+628.13%)
mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
Stars: ✭ 68 (+112.5%)
Keras GpKeras + Gaussian Processes: Learning scalable deep and recurrent kernels.
Stars: ✭ 218 (+581.25%)
sGDMLsGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
Stars: ✭ 86 (+168.75%)
Cornell MoeA Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
Stars: ✭ 198 (+518.75%)
FBNNCode for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
Stars: ✭ 67 (+109.38%)
Gpmp2Gaussian Process Motion Planner 2
Stars: ✭ 161 (+403.13%)
GPBoostCombining tree-boosting with Gaussian process and mixed effects models
Stars: ✭ 360 (+1025%)
LimboA lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)
Stars: ✭ 157 (+390.63%)
models-by-exampleBy-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
Stars: ✭ 43 (+34.38%)
Miscellaneous R CodeCode that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.
Stars: ✭ 146 (+356.25%)
mangoParallel Hyperparameter Tuning in Python
Stars: ✭ 241 (+653.13%)
Survival Analysis Using Deep LearningThis repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
Stars: ✭ 139 (+334.38%)
k2scK2 systematics correction using Gaussian processes
Stars: ✭ 15 (-53.12%)
AbolethA bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
Stars: ✭ 127 (+296.88%)
kalman-jaxApproximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
Stars: ✭ 84 (+162.5%)
GPimGaussian processes and Bayesian optimization for images and hyperspectral data
Stars: ✭ 29 (-9.37%)
GaussianprocessesPython3 project applying Gaussian process regression for forecasting stock trends
Stars: ✭ 78 (+143.75%)
SthenoGaussian process modelling in Python
Stars: ✭ 118 (+268.75%)
go-bayesoptA library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.
Stars: ✭ 47 (+46.88%)
Numpy MlMachine learning, in numpy
Stars: ✭ 11,100 (+34587.5%)
AutoForceSparse Gaussian Process Potentials
Stars: ✭ 17 (-46.87%)
GpflowGaussian processes in TensorFlow
Stars: ✭ 1,547 (+4734.38%)
boundary-gpKnow Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
Stars: ✭ 21 (-34.37%)
Neural TangentsFast and Easy Infinite Neural Networks in Python
Stars: ✭ 1,357 (+4140.63%)
surfinBHSurrogate Final BH properties
Stars: ✭ 14 (-56.25%)
GPflow-Slimcustomized GPflow with simple Tensorflow API
Stars: ✭ 17 (-46.87%)
periodicityUseful tools for periodicity analysis in time series data.
Stars: ✭ 15 (-53.12%)
modelsForecasting 🇫🇷 elections with Bayesian statistics 🥳
Stars: ✭ 24 (-25%)
hyper-enginePython library for Bayesian hyper-parameters optimization
Stars: ✭ 80 (+150%)
TemporalGPs.jlFast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html
Stars: ✭ 89 (+178.13%)