What is Bayesian deep learning?

Bayesian Deep Learning is a subfield of machine learning that combines deep learning models, such as neural networks, with Bayesian probability theory. This approach allows models to not only make predictions but also quantify uncertainty in those predictions, which is important for decision-making in areas like healthcare, autonomous vehicles, and finance. Bayesian Deep Learning typically involves using probabilistic methods to estimate the uncertainty of model parameters or predictions. This can lead to more robust and trustworthy AI systems, as they can communicate how confident they are in their outputs.