Matrix profile VI: Meaningful multidimensional motif discovery
Time series motifs are approximately repeating patterns in real-valued time series data.
They are useful for exploratory data mining and are often used as inputs for various time …
They are useful for exploratory data mining and are often used as inputs for various time …
NATSA: a near-data processing accelerator for time series analysis
Time series analysis is a key technique for extracting and predicting events in domains as
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …
A two-dimensional sparse matrix profile DenseNet for COVID-19 diagnosis using chest CT images
COVID-19 is a newly identified disease, which is very contagious and has been rapidly
spreading across different countries around the world, calling for rapid and accurate …
spreading across different countries around the world, calling for rapid and accurate …
[HTML][HTML] TCGAN: Convolutional Generative Adversarial Network for time series classification and clustering
F Huang, Y Deng - Neural Networks, 2023 - Elsevier
Recent works have demonstrated the superiority of supervised Convolutional Neural
Networks (CNNs) in learning hierarchical representations from time series data for …
Networks (CNNs) in learning hierarchical representations from time series data for …
[HTML][HTML] Concurrent time-series selections using deep learning and dimension reduction
The objective of this work was to investigate from a user perspective linkage between a 1D
time-series view of data and a 2D representation provided by dimension reduction …
time-series view of data and a 2D representation provided by dimension reduction …
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code
The recently introduced data structure, the Matrix Profile, annotates a time series by
recording the location of and distance to the nearest neighbor of every subsequence. This …
recording the location of and distance to the nearest neighbor of every subsequence. This …
A generalized matrix profile framework with support for contextual series analysis
Abstract The Matrix Profile is a state-of-the-art time series analysis technique that can be
used for motif discovery, anomaly detection, segmentation and others, in various domains …
used for motif discovery, anomaly detection, segmentation and others, in various domains …
Matrix profile xv: Exploiting time series consensus motifs to find structure in time series sets
In recent years the data mining community has largely coalesced around the idea that many
problems in time series analytics essentially reduce to finding and then reasoning about …
problems in time series analytics essentially reduce to finding and then reasoning about …
A novel matrix profile-guided attention LSTM model for forecasting COVID-19 cases in USA
Background: The outbreak of the novel coronavirus disease 2019 (COVID-19) has been
raging around the world for more than 1 year. Analysis of previous COVID-19 data is useful …
raging around the world for more than 1 year. Analysis of previous COVID-19 data is useful …
DragStream: an anomaly and concept drift detector in univariate data streams
AMSN Bibinbe, AJ Mahamadou… - … Conference on Data …, 2022 - ieeexplore.ieee.org
Anomaly detection in data streams comes with different technical challenges due to the data
nature. The main challenges include storage limitations, the speed of data arrival, and …
nature. The main challenges include storage limitations, the speed of data arrival, and …