Baran-phys/Tropical-Attention
[NeurIPS 2025] Official code for "Tropical Attention: Neural Algorithmic Reasoning for Combinatorial Algorithms"
This project offers a new way to solve complex computational problems in fields like phylogenetics, cryptography, and particle physics. It takes in structured data representing challenges like finding the shortest paths in a graph or optimally packing items, and outputs precise solutions or classifications. It's for researchers and practitioners in computationally intensive fields who need to tackle hard combinatorial problems more efficiently and accurately.
Use this if you are developing AI models for complex tasks that involve combinatorial optimization, graph theory, or resource allocation, and you need sharper, more robust, and faster solutions than traditional neural networks provide.
Not ideal if your primary goal is general-purpose natural language processing or image recognition, as this tool is specifically designed for neural algorithmic reasoning on structured, combinatorial problems.
Stars
27
Forks
2
Language
Python
License
MIT
Category
Last pushed
Oct 23, 2025
Commits (30d)
0
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