Stochastic refers to a variable process where the outcome involves some randomness and has some uncertainty. It is a mathematical term and is closely related to “randomness” and “probabilistic” and can be contrasted to the idea of “deterministic.” The stochastic nature of machine learning alg...
RBMs get their name due to there being “no communication between layers in the model, which is the ‘restriction’ of the model”36and that an RMB’s nodes “make ‘stochastic’ [or random] decisions”.36Because of this random process, RBMs are sometimes labeled as “stochastic neural netw...
The algorithms underlying deep neural networks–including backpropagation and stochastic gradient descent–have been around for a long time. So why is it that deep learning has only begun to show significant promise?Primarily it is because only now is it possible to provide these algorithms with ...
There is growing consensus in computational and systems neuroscience around the idea that the brain is apredictive machine, which uses internal (generative) models to continuously generate predictions in the service of perception, action and learning. One theory that is centred around this idea and w...
is the fact that perception, learning, and action all do the same thing—minimize free energy—but yet in different ways. Perception has a mind-to-world direction of fit: it operates by modifying internal states to make them more compatible with what is sensed. Learning has a mind-to-...