time seriesfamily
MQ-RNN and MQ-CNN
Multi-horizon quantile recurrent forecaster, demonstrated on forecasting demand for items sold on Amazon. Paper by Wen et al. (2017).
Levelfamily
Classtime series
Parametersnot in the notes
Contextnot in the notes
Released29 Nov 2017
Opennessopen source
Runs onnot in the notes
Statusactive
Industry Use Cases
Retail and Logistics
Demand forecastingR&D Topics
Identity
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
- other Sequence-to-sequence quantile forecaster with recurrent or convolutional encoder
- 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
- Apache License 2.0 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 GluonTS implementation (Apache-2.0).
- 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.
Links
DeveloperAmazonbig tech, USA
Amazonbig tech, USAModelMQ-RNN and MQ-CNNAmazon, time series
MQ-RNN and MQ-CNNAmazon, time seriesWho Runs Itnone recordedDeployments of these use cases; none names this model.
Use cases 1
Organisations 1
Sources
- arxiv.org/abs/1711.11053 https://arxiv.org/abs/1711.11053
- github.com/awslabs/gluonts https://github.com/awslabs/gluonts
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "MQ-RNN and MQ-CNN", https://aurion.semai.id/models/amazon-mq-rnn/, records of October 2026.