Groups
Category
Level
CTC loss trains sequence models when you do not know the alignment between inputs (frames) and outputs (labels).
Bayesian inference updates prior beliefs with observed data to produce a posterior distribution P(\theta\mid D).
Conditional probability measures the chance of event A happening when we already know event B happened.