4 papers
DISCCO: Distance-Based Bayesian Spatial Clustering of Complex Objects with Node-Frailty Centrality
Srijato Bhattacharyya, Huiyan Sang, Bani Mallick
Clustering problems increasingly involve complex objects observed over space, such as distributions, matrices, functions, images, or multivariate data, for which a scientifically m…
On Graph-Informed Distance Metrics for Comparing Graph Partitions
Srijato Bhattacharyya, Huiyan Sang, Bani Mallick
Comparing graph partitions is fundamental to the analysis of network-structured data, yet existing measures for comparing graph partitions typically rely on graph-agnostic indices…
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World
Bowen Lei, Dongkuan Xu, Ruqi Zhang +1
Sparse training has emerged as a promising method for resource-efficient deep neural networks (DNNs) in real-world applications. However, the reliability of sparse models remains a…
Integrative Variational Autoencoders for Generative Modeling of an Image Outcome with Multiple Input Images
Bowen Lei, Yeseul Jeon, Rajarshi Guhaniyogi +3
Understanding relationships across multiple imaging modalities is central to neuroimaging research. We introduce the Integrative Variational Autoencoder (InVA), the first hierarchi…