Recurrent recommender systems have been successful in capturing the temp...
Graph-structured data are ubiquitous. However, graphs encode diverse typ...
Normalizing flows transform a simple base distribution into a complex ta...
In this work, we propose a novel probabilistic sequence model that excel...
Event sequences can be modeled by temporal point processes (TPPs) to cap...
Recurrent neural networks have gained widespread use in modeling sequent...
Training recurrent neural networks (RNNs) on long sequence tasks is plag...
Inspired by the observation that humans are able to process videos
effic...
Vine copula models are a flexible tool in multivariate non-Gaussian
dist...
Existing methods for multi-domain image-to-image translation (or generat...
Handwriting of Chinese has long been an important skill in East Asia.
Ho...
Deep residual networks (ResNets) and their variants are widely used in m...
Recently, deep residual networks have been successfully applied in many
...