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Found 6 papers, 2 papers with code
A Review on MR Based Human Brain Parcellation Methods
Different methods have been developed and studied for constructing brain parcellations using different imaging modalities.
Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices
The locations of proton-proton collision points in LHC experiments are called primary vertices (PVs).
High Energy Physics - Experiment Data Analysis, Statistics and Probability
Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks
In many domains, there is significant interest in capturing novel relationships between time series that represent activities recorded at different nodes of a highly complex system.
Mining Sub-Interval Relationships In Time Series Data
In this paper, we define the notion of a sub-interval relationship (SIR) to capture inter- actions between two time series that are prominent only in certain sub-intervals of time.
Spatio-Temporal Data Mining: A Survey of Problems and Methods
Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains including, climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and Earth sciences.
Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data
Theory-guided data science (TGDS) is an emerging paradigm that aims to leverage the wealth of scientific knowledge for improving the effectiveness of data science models in enabling scientific discovery.
