Few-shot classification aims to learn a classifier to recognize unseen
c...
Imbalanced data pose challenges for deep learning based classification
m...
A topic model is often formulated as a generative model that explains ho...
Learning from set-structured data is a fundamental problem that has rece...
Observing a set of images and their corresponding paragraph-captions, a
...
We develop a recurrent gamma belief network (rGBN) for radar automatic t...
To simultaneously capture syntax and global semantics from a text corpus...
We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequent...
To train an inference network jointly with a deep generative topic model...