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vendor/ruvector/examples/exo-ai-2025/crates/exo-manifold/README.md
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# exo-manifold
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Continuous embedding space with SIREN networks for smooth manifold
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deformation in cognitive AI. Provides the geometric foundation that
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lets EXO-AI substrates represent and transform concepts as points on
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learned manifolds.
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## Features
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- **SIREN coordinate network** -- uses sinusoidal representation
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networks (SIREN) to learn implicit neural representations of
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continuous coordinate spaces with high-frequency detail.
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- **Manifold deformation** -- smoothly warps the embedding manifold to
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adapt cognitive geometry in response to new information, preserving
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local neighbourhood structure.
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- **Transfer prior store with domain-pair indexing** -- caches learned
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deformation priors indexed by (source, target) domain pairs so that
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cross-domain transfers start from an informed initialisation.
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## Quick Start
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Add the dependency to your `Cargo.toml`:
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```toml
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[dependencies]
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exo-manifold = "0.1"
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```
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Basic usage:
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```rust
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use exo_manifold::ManifoldEngine;
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use exo_core::{ManifoldConfig, Pattern};
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use burn::backend::NdArray;
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// Create engine with default SIREN parameters
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let config = ManifoldConfig::default();
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let device = Default::default();
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let mut engine = ManifoldEngine::<NdArray>::new(config, device);
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// Deform manifold with a high-salience pattern
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let pattern = Pattern { /* ... */ };
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engine.deform(pattern, 0.9)?;
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// Retrieve similar patterns via gradient descent
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let query = vec![/* embedding */];
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let results = engine.retrieve(&query, 10)?;
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// Strategic forgetting of low-salience regions
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engine.forget(0.5, 0.1)?;
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```
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## Crate Layout
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| Module | Purpose |
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|-------------|----------------------------------------------|
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| `network` | SIREN network definition and forward pass |
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| `retrieval` | Gradient descent retrieval algorithm |
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| `deform` | Manifold deformation and curvature regulation |
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| `forgetting`| Gaussian smoothing and weight pruning |
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| `transfer` | Prior store with domain-pair indexing |
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## Requirements
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- Rust 1.78+
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- Depends on `exo-core`, `burn`, `burn-ndarray`
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## Links
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- [GitHub](https://github.com/ruvnet/ruvector)
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- [EXO-AI Documentation](https://github.com/ruvnet/ruvector/tree/main/examples/exo-ai-2025)
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## License
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MIT OR Apache-2.0
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