#Bayesian-inference
Showing 55 of 55 repositories tagged #bayesian-inference, ranked by stars
Machine learning, in numpy
Bayesian Modeling and Probabilistic Programming in Python
Deep universal probabilistic programming with Python and PyTorch
A Python library that helps data scientists to infer causation rather than observing correlation.
Bayesian inference with probabilistic programming.
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
PyMC educational resources
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Awesome resources on normalizing flows.
Infer.NET is a framework for running Bayesian inference in graphical models
Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition
Learn about Machine Learning and Artificial Intelligence
A Library for Uncertainty Quantification.
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.
Gaussian processes in JAX and Equinox.
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
A resource list for causality in statistics, data science and physics
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
A Python package for building Bayesian models with TensorFlow or PyTorch
Bayesian Neural Field models for prediction in large-scale spatiotemporal datasets
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations
PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
bayes-toolbox
Bayesian Neural Network in PyTorch
:book: R 语言数据分析实战（写作中） Data Analysis in Action Using R
Automated Bayesian model discovery for time series data
Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
Bayesian dessert for Lasagne
Machine Learning - accelerated Bayesian inference
Machine learning assisted marginal likelihood (Bayesian evidence) estimation for Bayesian model selection
:octopus: Generalized additive models in Python with a Bayesian twist
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.
Nested Sampling post-processing and plotting
A colourful collection of codes and notebooks, like Planet Sakaar
A collection of educational notebooks covering key mathematical concepts and their applications in quantitative finance
Probabilistic programming with programmable inference for parallel accelerators.
Astrostatistics and Machine Learning class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
Fast Bayesian Inference in Python. 50+ conjugate models with vectorized updates, sufficient statistic helpers, built-in plotting, and SciPy integration.
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
A collection of datasets
Bayesian Inference and parameter estimation in quant finance.
A web interface for exploring PyMC3 traces
A collection of Methods and Models for various architectures of Artificial Neural Networks
Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.
A repository for recording the codes of machine learning algorithms
A straightforward Bayesian data fitting library
Library of composable generative population models which serve as the modeling and inference backend of BayesDB.
ChainoPy: A Python Library for Discrete Time Markov Chain based stochastic analysis
Adaptive Reinforcement Learning of curious AI basketball agents
BARNN: A Bayesian Autoregressive and Recurrent Neural Network - Official Repository