Project AURIONAI Use-Cases Research & Innovation
time seriesfamily

TCN (Temporal Convolutional Network)

Generic convolutional architecture for sequence modelling, shown to match or beat recurrent networks on many sequence tasks. Paper by Bai et al. (2018).

Carnegie Mellon University
Levelfamily
Classtime series
Parametersnot in the notes
Contextnot in the notes
Released4 Mar 2018
Opennessopen source
Runs onnot in the notes
Statusactive

R&D Topics

Identity

Developer
Carnegie Mellon University, Intel
Family
not in the notes
Released
4 Mar 2018 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 Causal dilated convolutions with residual blocks
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
MIT License 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' locuslab/TCN repository (MIT).
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.

Sources

  1. arxiv.org/abs/1803.01271 https://arxiv.org/abs/1803.01271
  2. github.com/locuslab/TCN https://github.com/locuslab/TCN
  3. nixtlaverse.nixtla.io/neuralforecast/docs/capabilities/overview.html https://nixtlaverse.nixtla.io/neuralforecast/docs/capabilities/overview.html
  4. modelzoo.co/model/tcn-pytorch https://modelzoo.co/model/tcn-pytorch
  5. huggingface.co/datasets/pwc-archive/methods https://huggingface.co/datasets/pwc-archive/methods
  6. arxiv.org/html/1803.01271 https://arxiv.org/html/1803.01271

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "TCN (Temporal Convolutional Network)", https://aurion.semai.id/models/tcn/, records of October 2026.