Project AURIONAI Use-Cases Research & Innovation
tabularfamily

GANDALF

Gated Adaptive Network for Deep Automated Learning of Features, a deep tabular model built from gated feature learning units. Paper by Joseph and Raj (2022).

Levelfamily
Classtabular
Parametersnot in the notes
Contextnot in the notes
Released18 Jul 2022
Opennessopen source
Runs onnot in the notes
Statusactive

R&D Topics

Identity

Developer
not in the notes
Family
not in the notes
Released
18 Jul 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 Gated feature learning units
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
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 pytorch-tabular implementation (MIT), maintained by the paper's first author. GATE (Gated Additive Tree Ensemble) is described in earlier versions of the same arXiv paper.
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/2207.08548 https://arxiv.org/abs/2207.08548
  2. github.com/pytorch-tabular/pytorch_tabular https://github.com/pytorch-tabular/pytorch_tabular
  3. github.com/manujosephv/pytorch_tabular https://github.com/manujosephv/pytorch_tabular
  4. arxiv.org/html/2207.08548 https://arxiv.org/html/2207.08548

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