sparseNMF Logo

Getting started

  • Installation
    • From PyPI (recommended)
    • From source
    • GPU support
    • Container
  • Quickstart
    • Standalone NMF
    • Joint NMF + autoencoder
    • Sample data
  • Tutorials
    • Tutorial 1 — Standalone sparse NMF
      • Fit the model
      • Reconstruction quality
      • Visualize the per-sample codes
      • Visualize the per-feature loadings
      • Next
    • Tutorial 2 — Joint NMF + autoencoder
      • Train
      • Plot the 2-D embedding
  • Examples

Reference

  • API reference
    • Standalone NMF
      • SparseNMF
        • SparseNMF.W
        • SparseNMF.H
        • SparseNMF.reconstruction_error_
        • SparseNMF.r2_score_
        • SparseNMF.r2_score_nonzero_
        • SparseNMF.n_iter_
        • SparseNMF.fit_transform()
        • SparseNMF.transform()
      • sparse_nmf()
      • train_sparse_nmf()
    • Joint model
      • SparseNMF_Autoencoder
        • SparseNMF_Autoencoder.encode()
        • SparseNMF_Autoencoder.forward()
        • SparseNMF_Autoencoder.reparameterize()
      • train_joint_model()
      • compute_joint_loss()
    • Attention analysis
      • extract_attention_weights()
      • extract_and_aggregate_attention()
      • trace_attention_to_genes()
      • compute_attention_correlation()
    • Visualization
      • plot_nmf_factor_distributions()
    • Sample data
      • generate_synthetic_sparse()
      • load_synthetic_sparse()
  • Prior works
    • Classic implementations
    • GPU implementations
    • Adjacent: deep generative factorization
    • Where this package fits
  • Changelog
    • v0.1.0 (initial)

Project

  • Contributing
    • Local setup
    • Filing an issue
    • Releases
  • License
sparseNMF
  • Index
  • Edit on GitHub

Index

C | E | F | G | H | L | N | P | R | S | T | W

C

  • compute_attention_correlation() (in module sparse_nmf)
  • compute_joint_loss() (in module sparse_nmf)

E

  • encode() (sparse_nmf.SparseNMF_Autoencoder method)
  • extract_and_aggregate_attention() (in module sparse_nmf)
  • extract_attention_weights() (in module sparse_nmf)

F

  • fit_transform() (sparse_nmf.SparseNMF method)
  • forward() (sparse_nmf.SparseNMF_Autoencoder method)

G

  • generate_synthetic_sparse() (in module sparse_nmf.data)

H

  • H (sparse_nmf.SparseNMF attribute)

L

  • load_synthetic_sparse() (in module sparse_nmf.data)

N

  • n_iter_ (sparse_nmf.SparseNMF attribute)

P

  • plot_nmf_factor_distributions() (in module sparse_nmf)

R

  • r2_score_ (sparse_nmf.SparseNMF attribute)
  • r2_score_nonzero_ (sparse_nmf.SparseNMF attribute)
  • reconstruction_error_ (sparse_nmf.SparseNMF attribute)
  • reparameterize() (sparse_nmf.SparseNMF_Autoencoder method)

S

  • sparse_nmf() (in module sparse_nmf)
  • SparseNMF (class in sparse_nmf)
  • SparseNMF_Autoencoder (class in sparse_nmf)

T

  • trace_attention_to_genes() (in module sparse_nmf)
  • train_joint_model() (in module sparse_nmf)
  • train_sparse_nmf() (in module sparse_nmf)
  • transform() (sparse_nmf.SparseNMF method)

W

  • W (sparse_nmf.SparseNMF attribute)

© Copyright 2026, Brian Schilder.

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