This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...
The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...
A Bayesian particle Gibbs framework enables unbiased spike time inference with millisecond resolution and jointly estimates uncertainties in both spike timing and model parameters from fast calcium ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results