Amortized Gaussian Process is a model that amortizes the computation of a Gaussian Process. With this model we can use autoencoder for time series with variable length and irregular sampling.
I am an ML researcher that is passionate, really passionate, about machine learning. I want to develop models capable of extracting the most information from the available data sources, and at the same time, can generalize to multiple tasks or target data distribution..
