Project AURIONAI Use-Cases Research & Innovation
Northeastern University
tabularfamily

ECOD

Unsupervised outlier detector that scores points by how extreme they are under each feature's empirical cumulative distribution. Paper by Li et al. (2022).

Figure from the ECOD paper: plot of normal points and outliers found by ECOD.
Levelfamily
Classtabular
Parametersnot in the notes
Contextnot in the notes
Released2 Jan 2022
Opennessunknown
Runs onnot in the notes
Statusactive

R&D Topics

Identity

Developer
Northeastern University, Carnegie Mellon University
Family
not in the notes
Released
2 Jan 2022 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
other Unsupervised, parameter-free; uses empirical cumulative distribution functions
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
table
Output
table
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
Implemented in PyOD (BSD-2-Clause).
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/2201.00382 https://arxiv.org/abs/2201.00382
  2. github.com/yzhao062/pyod https://github.com/yzhao062/pyod
  3. pyod.readthedocs.io/en/latest https://pyod.readthedocs.io/en/latest/
  4. arxiv.org/html/2201.00382 https://arxiv.org/html/2201.00382

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "ECOD", https://aurion.semai.id/models/ecod/, records of October 2026.