cleora
finalfusion-rust
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| cleora | finalfusion-rust | |
|---|---|---|
| 8 | 1 | |
| 472 | 86 | |
| 0.6% | - | |
| 2.4 | 6.3 | |
| 6 months ago | 7 months ago | |
| Jupyter Notebook | Rust | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cleora
- Cleora - an ultra fast graph embedding tool written in Rust
- Cleora.ai - open source general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data - new updates
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[R] Cleora: A Simple, Strong and Scalable Graph Embedding Scheme
Our team at Synerise AI has open sourced Cleora - an ultra fast vertex embedding tool for graphs & hypergraphs. If you've ever used node2vec, DeepWalk, LINE or similar methods - it might be worth to check it out.
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[R] Cleora - the fastest graph & hypergraph node embedding tool
A few weeks ago, our team at Synerise AI has open sourced Cleora - an ultra fast vertex embedding tool for graphs & hypergraphs. It is a tool, which can ingest any categorical, relational data and turn it into vector embeddings of entities. It is extremely fast, while offering very competitive quality of results. In fact, it may be the fastest hypergraph embedding tool possible in practice, without intentionally discarding/reducing input data.
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[D] Why I'm Lukewarm on Graph Neural Networks
Thanks for raising so many interesting points about model performance and complexity. In this context, I think our newly released graph embedding library - Cleora - might be of interest: https://github.com/Synerise/cleora Cleora has some nice performance-wise properties:
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Rusticles #20 - Wed Nov 18 2020
Synerise/cleora (Rust): Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
finalfusion-rust
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Compressing high-dimensional vectors by 97%
Nice article that explains product quantization very well!
PQ is really a nice compression technique. I implemented PQ and Optimized PQ [1] a while back in our word embedding package for Rust:
https://github.com/finalfusion/finalfusion-rust/
https://github.com/finalfusion/reductive/
Particularly Optimized PQ was effective in reducing vector sizes ~10 times with virtually no reconstruction loss. This made it much easier to ship models (no more 3GB embedding matrix with a neural net that is just a few megabytes large).
[1] http://kaiminghe.com/publications/pami13opq.pdf
What are some alternatives?
i3status-rust - Very resourcefriendly and feature-rich replacement for i3status, written in pure Rust
excalidraw-animate - A tool to animate Excalidraw drawings
Owlyshield - Owlyshield is an EDR framework designed to safeguard vulnerable applications from potential exploitation (C&C, exfiltration and impact).
magnitude - A fast, efficient universal vector embedding utility package.
node2vec-c - node2vec implementation in C++
excalidraw - Virtual whiteboard for sketching hand-drawn like diagrams
textsynth - A (unofficial) Rust wrapper for the TextSynth API.
GEM
yourcontrols - Shared cockpit for Microsoft Flight Simulator.
dog - A command-line DNS client.
ggez - Rust library to create a Good Game Easily
PyO3 - Rust bindings for the Python interpreter