849 Open source projects that are alternatives of or similar to Exoplanet

Full Bayesian Inference for Hidden Markov Models

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

Scalable 1D Gaussian Processes in C++, Python, and Julia

GPstuff - Gaussian process models for Bayesian analysis

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

Anything can happen in the next half hour (including spectral timing made easy)!

The Trendiness of Trends

Material for a workshop on Bayesian stats with R

A machine learning toolkit dedicated to time-series data

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

A didactic Gaussian process package for researchers in Jax.

Multi-core BUGS for fast Bayesian inference of large hierarchical models

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

A common framework for implementing and using log densities for inference.

A use-case focused tutorial for time series forecasting with python

Analyzes chronological patterns present in time-series data and provides human-readable descriptions

R-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.

K2 systematics correction using Gaussian processes

Useful tools for periodicity analysis in time series data.

A python multi-variate time series prediction library working with sklearn

nway -- Bayesian cross-matching of astronomical catalogues

A unified framework for machine learning with time series

Highly comparative time-series analysis

Bayesian Data Analysis demos for R

RStan, the R interface to Stan

Machine learning, in numpy

Nested Sampling post-processing and plotting

Bayesian Generalized Linear Models with Time-Varying Coefficients

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

Bayesian Data Analysis demos for Python

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Periodic time series analysis tools based on information theory

Examples for Bayesian inference using DynamicHMC.jl and related packages.

Probabilistic Programming with Gaussian processes in Julia

Code examples for pyFTS

Resources for working with time series and sequence data

A framework for historical volatility estimation and analysis.

Start with the Chempy tutorial

Particle filtering and sequential parameter inference in Python

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

A framework for systemic risk valuation and analysis.

Fast and flexible Gaussian Process regression in Python

List of awesome papers about time series, mainly including algorithms based on machine learning | 收录时间序列分析中各个研究领域的高水平文章，主要包含基于机器学习的算法

Fast and Easy Infinite Neural Networks in Python

High-performance Bayesian Data Analysis on the GPU in Clojure

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

A python module to detect stellar flares using Bayesian model comparison

AtsPy: Automated Time Series Models in Python (by @firmai)

Bayesian inference with probabilistic programming.

Distributed Bayesian Entity Resolution in Apache Spark

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

A Bayesian Analysis Toolkit in Julia

TSrepr: R package for time series representations

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

Axibase Time Series Database: Usage Examples and Research Articles

A high-level Bayesian analysis API written in Python