Probabilistic reasoning and statistical analysis in TensorFlow
☆4,417Mar 4, 2026Updated 2 weeks ago
Alternatives and similar repositories for probability
Users that are interested in probability are comparing it to the libraries listed below
Sorting:
- Deep universal probabilistic programming with Python and PyTorch☆8,991Jul 9, 2025Updated 8 months ago
- A probabilistic programming language in TensorFlow. Deep generative models, variational inference.☆4,842Mar 18, 2024Updated 2 years ago
- (Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.☆710Oct 4, 2021Updated 4 years ago
- Bayesian Modeling and Probabilistic Programming in Python☆9,530Updated this week
- Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.☆2,623Updated this week
- aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-firs…☆28,439Jun 25, 2024Updated last year
- Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more☆35,108Updated this week
- Gaussian processes in TensorFlow☆1,906May 29, 2025Updated 9 months ago
- Exploratory analysis of Bayesian models with Python☆1,797Updated this week
- TensorFlow-based neural network library☆9,906Feb 10, 2026Updated last month
- A highly efficient implementation of Gaussian Processes in PyTorch☆3,850Mar 12, 2026Updated last week
- A simple probabilistic programming language.☆709Jan 9, 2026Updated 2 months ago
- Efficiently computes derivatives of NumPy code.☆7,464Updated this week
- Model analysis tools for TensorFlow☆1,268Aug 6, 2025Updated 7 months ago
- Bayesian optimization in PyTorch☆3,481Updated this week
- Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.☆10,854Nov 4, 2024Updated last year
- A collection of infrastructure and tools for research in neural network interpretability.☆4,703Feb 6, 2023Updated 3 years ago
- Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. …☆2,727Mar 12, 2026Updated last week
- Input pipeline framework☆989Aug 6, 2025Updated 7 months ago
- Build Graph Nets in Tensorflow☆5,394Dec 12, 2022Updated 3 years ago
- Probabilistic Torch is library for deep generative models that extends PyTorch☆894May 12, 2024Updated last year
- A game theoretic approach to explain the output of any machine learning model.☆25,131Mar 12, 2026Updated last week
- TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.☆2,995Jan 16, 2026Updated 2 months ago
- Statsmodels: statistical modeling and econometrics in Python☆11,297Mar 12, 2026Updated last week
- Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.☆17,062Jun 2, 2023Updated 2 years ago
- BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.☆1,030Feb 3, 2026Updated last month
- TensorFlow's Visualization Toolkit☆7,121Mar 9, 2026Updated last week
- JAX-based neural network library☆3,197Mar 12, 2026Updated last week
- Google Research☆37,452Mar 12, 2026Updated last week
- TensorFlow Reinforcement Learning☆3,136Dec 8, 2022Updated 3 years ago
- Notebooks about Bayesian methods for machine learning☆1,911Mar 6, 2024Updated 2 years ago
- Models and examples built with TensorFlow☆77,687Mar 11, 2026Updated last week
- A Python toolbox for performing gradient-free optimization☆4,161Updated this week
- Python code for "Probabilistic Machine learning" book by Kevin Murphy☆7,034Feb 26, 2026Updated 3 weeks ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆7,999Updated this week
- Deep Learning for humans☆63,935Updated this week
- Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.☆14,679Dec 1, 2025Updated 3 months ago
- Fast and flexible AutoML with learning guarantees.☆3,457Nov 30, 2023Updated 2 years ago
- Fast, flexible and easy to use probabilistic modelling in Python.☆3,512Mar 6, 2025Updated last year