Bayesian Feature Extraction using Gaussian and Diffused-gamma Priors for High Dimensional Spatio-Temporal Data

arXiv:2607.24378 · stat.ME, q-bio.QM, stat.AP, stat.CO, stat.ML · Submitted 2026-07-27 · Read on arXiv

Garrett Frady, Dipak K. Dey, Shariq Mohammed

stat.ME, q-bio.QM, stat.AP, stat.CO, stat.ML

Submitted: 2026-07-27

Code: https://github.com/garrett-frady/gdprior

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Feature Extraction — 33× in this paper · explained in 3 episodes
Lasso — 32× in this paper · explained in 2 episodes
Sparsity — 25× in this paper · explained in 5 episodes
Loss Function — 20× in this paper · explained in 2 episodes
Feature Selection — 19× in this paper · explained in 4 episodes
AUC — 18× in this paper · explained in 2 episodes
Accuracy — 12× in this paper · explained in 1 episode
Clustering — 12× in this paper · explained in 2 episodes
Regularization — 10× in this paper · explained in 3 episodes
K-means Clustering — 7× in this paper · explained in 3 episodes
Gaussian and Diffused-gamma — 4× in this paper
Computational Efficiency — 3× in this paper · explained in 2 episodes
Hyperparameters — 3× in this paper · explained in 2 episodes
Robustness — 3× in this paper · explained in 6 episodes
Bayesian Framework — 2× in this paper · explained in 3 episodes
Core — 2× in this paper · explained in 2 episodes
Editor — 2× in this paper · explained in 2 episodes
Interpretability — 2× in this paper · explained in 15 episodes
Principal Component Analysis (PCA) — 2× in this paper · explained in 8 episodes
Abundance — 1× in this paper · explained in 1 episode
Coherence — 1× in this paper · explained in 2 episodes
Computational overhead — 1× in this paper · explained in 2 episodes
Curse of Dimensionality — 1× in this paper · explained in 6 episodes
Latent Variables — 1× in this paper · explained in 2 episodes
Temporal Correlations — 1× in this paper · explained in 2 episodes

Terminology

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