Soft-MSM is a smooth, gradient-enabled version of the context-aware MSM distance for time series alignment that outperforms Soft-DTW alternatives in clustering and nearest-centroid classification.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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Presents the bixplot as an extension of the boxplot incorporating contiguous clustering to visualize bimodality and multimodality while displaying individual data points, with Python and R implementations.
NPAP is a Python package built on NetworkX that supplies 13 partitioning strategies and two aggregation profiles for network graph reduction via a strategy pattern allowing custom extensions.
citing papers explorer
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Soft-MSM: Differentiable Context-Aware Elastic Alignment for Time Series
Soft-MSM is a smooth, gradient-enabled version of the context-aware MSM distance for time series alignment that outperforms Soft-DTW alternatives in clustering and nearest-centroid classification.
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The bixplot: A variation on the boxplot suited for bimodal data
Presents the bixplot as an extension of the boxplot incorporating contiguous clustering to visualize bimodality and multimodality while displaying individual data points, with Python and R implementations.
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NPAP: Network Partitioning and Aggregation Package for Python
NPAP is a Python package built on NetworkX that supplies 13 partitioning strategies and two aggregation profiles for network graph reduction via a strategy pattern allowing custom extensions.