Time Series Streams

3 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary Coding

eXascaleInfolab/CORAD Big Data 2019

In this work, we demonstrate how one can leverage the correlation across several related time series streams to both drastically improve the compression efficiency and reduce the accuracy loss. We present a novel compression algorithm for time series streams called CORAD (CORelation-Aware compression of time series streams based on sparse Dictionary coding).

ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams

eXascaleInfolab/orbits Proceedings of the VLDB Endowment (PVLDB) 2020

In this paper, we introduce a new online recovery technique to recover multiple time series streams in linear time.

INSTANCE – the Italian seismic dataset for machine learning

INGV/instance Earth System Science Data 2021

The Italian earthquake waveform data are collected here in a dataset suited for machine learning analysis (ML) applications.