Structure-Preserving Correction Learning for Sparse Bayesian Inference in Brain Source Imaging

arXiv:2606.07196 · cs.LG · Submitted 2026-06-05 · Read on arXiv

cs.LG

Submitted: 2026-06-05

Updated: 2026-10-15

Comments: preprint

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

Terminology

• Hyperparameters — 18× in this paper · explained in 2 episodes
• Sparse Bayesian Learning — 9× in this paper
• Sparsity — 8× in this paper · explained in 4 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Bayesian Inference — 6× in this paper · explained in 5 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Deep Supervision — 4× in this paper · explained in 2 episodes
• Interpretability — 4× in this paper · explained in 15 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Parameterization — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Bayesian Framework — 2× in this paper · explained in 3 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Papers — 2× in this paper · explained in 3 episodes
• Signal-to-Noise Ratios — 2× in this paper
• Active Regions — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Heteroscedasticity — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Transferability — 1× in this paper · explained in 5 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Sparse Bayesian Learning for DOA Estimation in Heteroscedastic Noise
• Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures

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