A Python package for causal inference in quasi-experimental settings
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Updated
Jun 28, 2024 - Python
A Python package for causal inference in quasi-experimental settings
A fast and easy to use, moddable, Python based Minecraft server!
Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.
Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference
An example plugin for the PyMine-Server plugin system
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Distributed differentiable graph computation using PyTensor
Bicyclus, a Bayesian Inference module for Cyclus
Replication materials for "The Relational Bases of Informal Financial Cooperation" (Simpson, In Prep.)
Demonstrating the use of behavior-driven development (BDD) to Bayesian growth models for assumption tracking.
Python package of the 'Tumoroscope' model implemented in PyMC.
Minecraft BE Edition Python Scripts
Testing deployment of PyMC models using MLFlow and BentoML.
Python version of McElreath's Statistical Rethinking package
My algorithms implementation to discover the main themes that pervade a large and otherwise unstructured collection of documents.
demonstration of uni-variate time series prediction by predicting monthly births in Sweden for the next 12 months
A comparison between Bayesian Neural Network and Classical Neural Network
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