A Bayesian network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG).

2017-05-23 · In this post I’m going to introduce Bayesian deep learning (BDL), which provides a deep learning framework which can also model uncertainty.

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2020-01-11 · What makes Bayesian inference distinctive, and why Bayesian inference is worthwhile in deep learning.

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2020-01-22 · We show that if the prior does not distinguish between functions that generalize and functions that don’t, Bayesian inference cannot provide uncertainties.

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2020-05-05 · Breaking Bayesian Optimization into small, sizeable chunks.

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2020-04-03 · Bayesian Layers in Torch Zoo is a simple and extensible library to create Bayesian Neural Network layers on the top of PyTorch.

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BaaL is an active learning library by ElementAI. This repository contains techniques and reusable components to make active learning accessible for all.

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DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions.

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