6 citations · 8 across the 5 of their papers we have counts for
5 papers
SkipSNN: Efficiently Classifying Spike Trains with Event-attention
Hang Yin, Yao Su, Liping Liu +3
Spike train classification has recently become an important topic in the machine learning community, where each spike train is a binary event sequence with \emph{temporal-sparsity…
Multi-State Brain Network Discovery
Hang Yin, Yao Su, Xinyue Liu +3
Brain network discovery aims to find nodes and edges from the spatio-temporal signals obtained by neuroimaging data, such as fMRI scans of human brains. Existing methods tend to de…
A General Modeling Framework for Network Autoregressive Processes
Hang Yin, Abolfazl Safikhani, George Michailidis
The paper develops a general flexible framework for Network Autoregressive Processes (NAR), wherein the response of each node linearly depends on its past values, a prespecified li…
On the Impact of Spurious Correlation for Out-of-distribution Detection
Yifei Ming, Hang Yin, Yixuan Li
Modern neural networks can assign high confidence to inputs drawn from outside the training distribution, posing threats to models in real-world deployments. While much research at…
Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks
Hang Yin, Xinyue Liu, Xiangnan Kong
Sparse inverse covariance estimation (i.e., edge de-tection) is an important research problem in recent years, wherethe goal is to discover the direct connections between a set ofn…