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Found 4 papers, 0 papers with code
Seismic-phase detection using multiple deep learning models for global and local representations of waveforms
Finally, in an application to low-frequency earthquakes, we demonstrated the flexibility of the proposed method, which is readily adaptable for the detection of low-frequency earthquakes by retraining only a local model.
Discovering the neural correlate informed nosological relation among multiple neuropsychiatric disorders through dual utilisation of diagnostic information
The unravelled nosological relation among diverse types of neuropsychiatric disorders serves as an important precursor in advocating the dimensional approach to psychiatric classification.
Multiple-view clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization
However, when one applies an existing multiple-view clustering method to fMRI data, there is a need to simplify the data structure, independently dealing with elements in a FC matrix, i. e., vectorizing a correlation matrix.
Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions
We propose a novel method for multiple clustering that assumes a co-clustering structure (partitions in both rows and columns of the data matrix) in each view.
