GustikS / NeuraLogic
Deep relational learning through differentiable logic programming.
Why this job: works in the areas we cover, but does not say which job it does
What it does
At the core of the framework, there is a custom language you can use to write differentiable programs encoding your learning scenarios, similarly to classic Deep Learning (DL) frameworks (e.g. TensorFlow). However, the language follows a logic programming paradigm and is declarative in nature (it's similar to Datalog). This means that instead of directly encoding the computation graph, you just _declare_:
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 42 days ago
- Stars
- 122
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.3.0
- Released 4 years ago
- Built with
- Java
- 98% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 39 merged
- 1 waiting
- Releases
- 2
- 0 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Java 98%
- Python 2%
- ANTLR <1%
Topics
- deep-learning
- differentiable-programming
- logic-programming
- machine-learning
- relational-learning
Project record
- JobOther AI tools
- StatusListed
- Commits611
- Forks15
- Watching4
- Stars in 28 days0
- CreatedFeb 21, 2018
- First seen by usNov 7, 2026
- CheckedNov 8, 2026