Showing 4 of 4 projects
A Python library for probabilistic modeling built on PyTorch, offering modular distributions, GPU support, and flexible model composition.
A Python toolkit for causal and probabilistic reasoning using graphical models like Bayesian Networks and Structural Equation Models.
TensorFlow and NumPy implementations of HMM Viterbi and forward/backward algorithms for sequence modeling.
A Julia library for representation, inference, and learning in Bayesian networks.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.