This talk will be about Recurrent Neural Networks, and some examples of applications. Compared to standard neural networks, which take in an input vector of fixed size, Recurrent Neural Networks are useful in being able to process sequences of input vectors (e.g. letters, time series data, and video frames) Speaker(s): Brian Chen (University of Michigan)
Building: | East Hall |
---|---|
Event Type: | Workshop / Seminar |
Tags: | Mathematics |
Source: | Happening @ Michigan from Department of Mathematics |