Glow
E736216
Glow is a generative flow-based model architecture used for high-quality image and audio synthesis through invertible transformations.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Glow canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8483181 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glow Context triple: [WaveGlow, basedOn, Glow]
-
A.
Glow
"Glow" is a song featured on Kelly Clarkson's holiday album "When Christmas Comes Around..." that showcases her soulful vocals in a festive, contemporary pop setting.
-
B.
Glow
"Glow" is a track by the artist Tasty, likely featuring an energetic, electronic-influenced sound characteristic of their music style.
-
C.
Glitter
Glitter is a 2001 musical romantic drama film starring Mariah Carey as an aspiring singer navigating love and the music industry in 1980s New York City.
-
D.
Glitter
"Glitter" is an introspective, genre-blending EP by 070 Shake that helped establish her as a distinctive voice in contemporary hip-hop and alternative R&B.
-
E.
Glitz
Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glow Target entity description: Glow is a generative flow-based model architecture used for high-quality image and audio synthesis through invertible transformations.
-
A.
Glow
"Glow" is a song featured on Kelly Clarkson's holiday album "When Christmas Comes Around..." that showcases her soulful vocals in a festive, contemporary pop setting.
-
B.
Glow
"Glow" is a track by the artist Tasty, likely featuring an energetic, electronic-influenced sound characteristic of their music style.
-
C.
Glitter
Glitter is a 2001 musical romantic drama film starring Mariah Carey as an aspiring singer navigating love and the music industry in 1980s New York City.
-
D.
Glitter
"Glitter" is an introspective, genre-blending EP by 070 Shake that helped establish her as a distinctive voice in contemporary hip-hop and alternative R&B.
-
E.
Glitz
Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
deep generative model
ⓘ
flow-based generative model architecture ⓘ normalizing flow model ⓘ |
| appliedIn |
audio processing
ⓘ
computer vision ⓘ |
| basedOn | normalizing flows ⓘ |
| canBeAppliedTo |
audio synthesis
ⓘ
speech modeling ⓘ |
| comparedWith |
GANs
NERFINISHED
ⓘ
VAEs ⓘ |
| extends | RealNVP NERFINISHED ⓘ |
| field | machine learning ⓘ |
| hasAbbreviation | Glow NERFINISHED ⓘ |
| hasArchitectureComponent |
coupling layers
ⓘ
invertible 1x1 convolution layers ⓘ split operations ⓘ squeezing operations ⓘ |
| hasAuthor |
Diederik P. Kingma
NERFINISHED
ⓘ
Prafulla Dhariwal NERFINISHED ⓘ |
| hasEvaluationMetric |
bits per dimension
ⓘ
log-likelihood ⓘ |
| hasInfluenced | subsequent normalizing flow models ⓘ |
| hasKeyProperty |
efficient sampling
ⓘ
exact log-likelihood computation ⓘ invertible transformations ⓘ parallelizable architecture ⓘ tractable inference ⓘ |
| hasKeyTechnique |
actnorm layers
ⓘ
affine coupling layers ⓘ invertible 1x1 convolutions ⓘ multi-scale architecture ⓘ |
| hasLatentSpace | continuous latent variables ⓘ |
| hasProperty |
scalable to high-resolution images
ⓘ
supports conditional generation ⓘ |
| hasPublicationYear | 2018 ⓘ |
| hasTitle | Glow: Generative Flow with Invertible 1x1 Convolutions NERFINISHED ⓘ |
| hasTrainingObjective | maximum likelihood estimation ⓘ |
| implementedIn |
PyTorch
NERFINISHED
ⓘ
TensorFlow NERFINISHED ⓘ |
| improvesOver | RealNVP NERFINISHED ⓘ |
| publishedAt | International Conference on Machine Learning NERFINISHED ⓘ |
| subfield | deep generative modeling ⓘ |
| supports | exact latent-variable inference ⓘ |
| usedFor |
image editing
ⓘ
image generation ⓘ image synthesis ⓘ latent space interpolation ⓘ representation learning ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Glow Description of subject: Glow is a generative flow-based model architecture used for high-quality image and audio synthesis through invertible transformations.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.