Optax
E438357
Optax is a gradient processing and optimization library for JAX, providing a flexible collection of composable optimizers and transformations for training machine learning models.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Optax canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4425384 — 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: Optax Context triple: [JAX, compatibleWith, Optax]
-
A.
Opekta
Opekta was a German-Dutch company that produced and sold pectin-based gelling agents for making jam, notably managed in its Amsterdam branch by Anne Frank’s father, Otto Frank.
-
B.
Phenax
Phenax is a small genus of flowering plants in the hemp family Cannabaceae, native to the Americas and typically found in tropical to subtropical regions.
-
C.
Versonnex
Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
D.
Plaxtol
Plaxtol is a small rural village and civil parish in Kent, England, known for its historic buildings and surrounding countryside.
-
E.
Ornex
Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
- 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: Optax Target entity description: Optax is a gradient processing and optimization library for JAX, providing a flexible collection of composable optimizers and transformations for training machine learning models.
-
A.
Opekta
Opekta was a German-Dutch company that produced and sold pectin-based gelling agents for making jam, notably managed in its Amsterdam branch by Anne Frank’s father, Otto Frank.
-
B.
Phenax
Phenax is a small genus of flowering plants in the hemp family Cannabaceae, native to the Americas and typically found in tropical to subtropical regions.
-
C.
Versonnex
Versonnex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
D.
Plaxtol
Plaxtol is a small rural village and civil parish in Kent, England, known for its historic buildings and surrounding countryside.
-
E.
Ornex
Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
JAX ecosystem library
ⓘ
machine learning library ⓘ open-source software ⓘ software library ⓘ |
| compatibleWith |
jax.grad
ⓘ
jax.jit ⓘ jax.pmap ⓘ jax.vmap ⓘ |
| designGoal |
compatibility with JAX transformations
ⓘ
composability of optimization components ⓘ functional programming style API ⓘ separation of model definition and optimization logic ⓘ |
| documentationFormat |
examples and tutorials
ⓘ
online API reference ⓘ |
| ecosystem | DeepMind JAX ecosystem NERFINISHED ⓘ |
| feature |
adaptive gradient methods
ⓘ
composable optimizers ⓘ gradient clipping ⓘ gradient transformations ⓘ learning rate schedules ⓘ loss scaling utilities ⓘ momentum methods ⓘ multi-device training utilities ⓘ parameter regularization ⓘ second-order optimization utilities ⓘ stateful and stateless transformations ⓘ stochastic gradient descent variants ⓘ |
| isFreeAndOpenSource | true ⓘ |
| license | Apache License 2.0 ⓘ |
| primaryDomain |
gradient-based optimization
ⓘ
optimization for machine learning ⓘ |
| programmingLanguage | Python ⓘ |
| providesOptimizer |
adafactor
NERFINISHED
ⓘ
adagrad ⓘ adam NERFINISHED ⓘ adamw ⓘ lamb ⓘ lars ⓘ novograd NERFINISHED ⓘ rmsprop NERFINISHED ⓘ sgd ⓘ yogi ⓘ |
| repositoryPlatform | GitHub NERFINISHED ⓘ |
| supportsFramework | JAX NERFINISHED ⓘ |
| supportsUseCase |
large-scale distributed training
ⓘ
reinforcement learning optimization ⓘ research prototyping in optimization ⓘ training neural networks ⓘ |
| typicalWorkflow | init-update functional optimizer API ⓘ |
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: Optax Description of subject: Optax is a gradient processing and optimization library for JAX, providing a flexible collection of composable optimizers and transformations for training machine learning models.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.