Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...

New NASA-level software framework reproduces DUT vs ΛCDM results, resolving Hubble and growth tensions with Δχ² = ...

Python companion package for the textbook: Generative Bayesian Computation: Quantile Neural Networks for Inference and Surrogates Nicholas Polson (University of Chicago) & Vadim Sokolov (George Mason ...

This is an unambitious Python library for working with Bayesian networks. For serious usage, you should probably be using a more established project, such as pomegranate, pgmpy, bnlearn (which is ...

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