Minimal t-distributed stochastic neighbor embedding (t-SNE) implementation in JAX.
Project description
TSNEx
TSNEx is a lightweight, high-performance Python library for t-Distributed Stochastic Neighbor Embedding (t-SNE) built on top of JAX. Leveraging the power of JAX, tsnex
offers JIT compilation, automatic differentiation, and hardware acceleration support to efficiently handle high-dimensional data for visualization and clustering tasks.
Installation
Use the package manager pip to install tsnex
.
pip install tsnex
Usage
import tsnex
# Generate some high-dimensional data
key = jax.random.key(0)
X = jax.random.normal(key, shape=(10_000, 50))
# Perform t-SNE dimensionality reduction
X_embedded = tsnex.transform(X, n_components=2)
Contributing
We welcome contributions to TSNEx! Whether it's adding new features, improving documentation, or reporting issues, please feel free to make a pull request and/or open an issue.
License
TSNEx is licensed under the MIT License. See the file for more details.
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