For users experiencing the "Tensor in" & "Tensor out" approach to Deep Learning Inference, getting started with Triton can lead to many questions. The goal of this repository is to familiarize users ...

: The posterior; the probability of the hypothesis (e.g. that a parameter has a certain value) given the data: The likelihood of observing/generating the data given the hypothesis: The prior ...

If you are interested in learning more about machine learning inference on the recently launched Raspberry Pi Pico microcontroller, you may be interested in a new project published to the Hackster.io ...

Abstract: Probabilistic graphical models are useful for modelling stochastic phenomena for doing inferences and reasoning under uncertainty. Especially, chain graph models and Bayesian networks can be ...