Algebraic Signatures for Structural Learning in Probability Tensors

arXiv:2607.18817 · stat.ML, cs.LG · Submitted 2026-07-21 · Read on arXiv

Akihiro Maeda, Shohei Hidaka, Satoshi Aoki

stat.ML, cs.LG

Submitted: 2026-07-21

Comments: Submitted to Algebraic Statistics

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

Terminology

• Accuracy — 15× in this paper · explained in 1 episode
• Conditional Independence — 15× in this paper · explained in 2 episodes
• Core — 14× in this paper · explained in 2 episodes
• Composition — 12× in this paper · explained in 2 episodes
• Calibration — 6× in this paper · explained in 9 episodes
• Algebraic Signature Analysis — 5× in this paper
• Minimum Invariant Constraint — 5× in this paper
• Inverse Problem — 4× in this paper · explained in 2 episodes
• Editor — 3× in this paper · explained in 2 episodes
• Expressivity — 3× in this paper · explained in 2 episodes
• Compositionality — 2× in this paper · explained in 2 episodes
• Elias — 2× in this paper · explained in 2 episodes
• False Negatives — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Hamming Distance — 2× in this paper · explained in 2 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Mechanistic Interpretability — 2× in this paper · explained in 4 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Vector Representations — 2× in this paper · explained in 2 episodes
• Admissibility — 1× in this paper · explained in 2 episodes
• Akaike Information Criterion — 1× in this paper
• Bayesian Information Criterion — 1× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Computational Efficiency — 1× in this paper · explained in 2 episodes
• Conformity — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Geometric Distribution — 1× in this paper · explained in 2 episodes
• Information-Theoretic Framework — 1× in this paper · explained in 2 episodes
• Learning Paradigms — 1× in this paper · explained in 2 episodes
• Likelihood-based framework — 1× in this paper · explained in 2 episodes
• Localization — 1× in this paper · explained in 2 episodes
• Mutual Information — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Pointwise Mutual Information (PMI) — 1× in this paper · explained in 4 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Scale-Invariance — 1× in this paper · explained in 2 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Real birational implicitization for statistical models

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