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Time Series Clustering

5 papers with code · Time Series

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SOM-VAE: Interpretable Discrete Representation Learning on Time Series

ICLR 2019 JustGlowing/minisom

We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two macro states, as well as on a challenging real world medical time series application on the eICU data set.

DIMENSIONALITY REDUCTION REPRESENTATION LEARNING TIME SERIES TIME SERIES CLUSTERING

Time Series Clustering via Community Detection in Networks

19 Aug 2015lnferreira/time_series_clustering_via_community_detection

In this paper, we propose a technique for time series clustering using community detection in complex networks.

COMMUNITY DETECTION TIME SERIES TIME SERIES ANALYSIS TIME SERIES CLUSTERING

N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding

16 Aug 2019rymc/n2d

We study a number of local and global manifold learning methods on both the raw data and autoencoded embedding, concluding that UMAP in our framework is best able to find the most clusterable manifold in the embedding, suggesting local manifold learning on an autoencoded embedding is effective for discovering higher quality discovering clusters.

IMAGE CLUSTERING REPRESENTATION LEARNING TIME SERIES TIME SERIES CLUSTERING

Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation

18 Oct 2015avishaiwa/SPARCWave

We propose a simple and efficient time-series clustering framework particularly suited for low Signal-to-Noise Ratio (SNR), by simultaneous smoothing and dimensionality reduction aimed at preserving clustering information.

DIMENSIONALITY REDUCTION TIME SERIES TIME SERIES CLUSTERING