High-Performance Implementation of Spectral Learning of Latent-Variable PCFGs (Cohen et al., 2013)
-
Updated
Apr 11, 2021 - Python
#
spectral-learning
Here are 5 public repositories matching this topic...
A Python package implementing Rectified Spectral Units (ReSUs), a biologically inspired neural building block for backprop-free training using spectral decomposition and Canonical Correlation Analysis (CCA).
-
Updated
Jan 31, 2026 - Python
A from-scratch implementation of Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) using NumPy. Explores dimensionality reduction, linear algebra, and clustering on the Wine Quality dataset.
python data-science machine-learning numpy linear-algebra pca dimensionality-reduction svd wine-quality spectral-learning
-
Updated
Apr 22, 2026 - Python
A neural architecture framework exploring low-rank multiplicative gating, spectral orthogonal bases (DCT/Walsh), complex-valued phase mixers, and conformal geometry over frozen substrates. Learning to equalize, not to sculpt.
pytorch neural-networks discrete-cosine-transform hyperbolic-geometry conformal-mapping low-rank-approximation poincare-disk walsh-hadamard spectral-learning complex-valued-neural-networks parameter-efficient-tuning hardware-efficiency
-
Updated
Jul 19, 2026 - Python
Simple spectral learning for weighted automata
-
Updated
Jan 19, 2026 - Python
Improve this page
Add a description, image, and links to the spectral-learning topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the spectral-learning topic, visit your repo's landing page and select "manage topics."