time series
Conv-AE
Convolutional autoencoder anomaly detector, top of the SKAB outlier leaderboard.
Levelmodel
Classtime series
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessunknown
Runs onnot in the notes
Statusnot in the notes
Benchmark Results
maintainer-run
SKABtime series
Outlier detection leaderboardmaintainer-run
0.78
00.40.8
Score in F1. Higher is better.
rank 1
Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).
Industry Use Cases
R&D Topics
Identity
- Developer
- not in the notes
- Family
- not in the notes
- Released
- – sources
- Weights published
- –
- Record checked
- 10 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
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- time series
- Output
- not in the notes
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
- unknown
- Licence
- not in the notes 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
- not in the notes
- 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.
Lineage
The notes record no lineage for this model.
Links
Developersnone recorded
ModelConv-AEtime series
Who Runs It
PT Pertamina Hulu Rokan (PHR)In production, 17 Oct 2025Deployments of these use cases; none names this model.
PT Pertamina Hulu Rokan (PHR)In production, 17 Oct 2025Deployments of these use cases; none names this model.Sources
- GitHub - waico/SKAB: SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms. github.com https://github.com/waico/SKAB
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Conv-AE", https://aurion.semai.id/models/conv-ae/, records of October 2026.