49 citations · 241 across the 42 of their papers we have counts for
6 papers · 1 filter
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Coping with distributional shifts is an important part of transfer learning methods in order to perform well in real-life tasks. However, most of the existing approaches in this ar…
Coping with Change: Learning Invariant and Minimum Sufficient Representations for Fine-Grained Visual Categorization
Shuo Ye, Shujian Yu, Wenjin Hou +2
Fine-grained visual categorization (FGVC) is a challenging task due to similar visual appearances between various species. Previous studies always implicitly assume that the traini…
Higher-order Organization in the Human Brain from Matrix-Based Rényi's Entropy
Qiang Li, Shujian Yu, Kristoffer H Madsen +2
Pairwise metrics are often employed to estimate statistical dependencies between brain regions, however they do not capture higher-order information interactions. It is critical to…
Causal Recurrent Variational Autoencoder for Medical Time Series Generation
Hongming Li, Shujian Yu, Jose Principe
We propose causal recurrent variational autoencoder (CR-VAE), a novel generative model that is able to learn a Granger causal graph from a multivariate time series x and incorporat…
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making
Shujian Yu, Hongming Li, Sigurd Løkse +2
The Cauchy-Schwarz (CS) divergence was developed by Príncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional di…
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis
Kaizhong Zheng, Shujian Yu, Badong Chen
There is a recent trend to leverage the power of graph neural networks (GNNs) for brain-network based psychiatric diagnosis, which,in turn, also motivates an urgent need for psychi…