time seriesfamily
ROCKET
Fast time series classification method that transforms series with many random convolutional kernels and trains a linear classifier. Paper by Dempster et al. (2019).
Levelfamily
Classtime series
Parametersnot in the notes
Contextnot in the notes
Released29 Oct 2019
Opennessopen source
Runs onnot in the notes
Statusactive
Identity
- Developer
- Monash University
- Family
- not in the notes
- Released
- 29 Oct 2019 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- CNN Random convolutional kernels feeding a linear classifier
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- time series
- Output
- time series
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open source
- Licence
- GNU General Public License v3.0 sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Licence is that of the authors' angus924/rocket repository (GPL-3.0).
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModelROCKETMonash University, time series
ROCKETMonash University, time seriesUse CasesIndustrial Forecasting (Load, Throughput, Demand)IndustrialDemand ForecastingRetail and LogisticsUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs Itnone recordedDeployments of these use cases; none names this model.
Organisations 1
Sources
- arxiv.org/abs/1910.13051 https://arxiv.org/abs/1910.13051
- github.com/angus924/rocket https://github.com/angus924/rocket
- huggingface.co/datasets/pwc-archive/methods https://huggingface.co/datasets/pwc-archive/methods
- arxiv.org/html/1910.13051 https://arxiv.org/html/1910.13051
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "ROCKET", https://aurion.semai.id/models/rocket/, records of October 2026.