Neural-Bayesian Structure Learning for Discrete Choice Modeling

arXiv:2608.25258 · cs.LG, cs.AI · Submitted 2026-08-26 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/HyunsooYun/neural-bsl

Terminology

• Benchmark — 11× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Adjacency Matrix — 5× in this paper · explained in 1 episode
• Topological Order — 4× in this paper · explained in 2 episodes
• Causal Discovery — 3× in this paper · explained in 2 episodes
• Causal Inference — 3× in this paper · explained in 4 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Score Function — 3× in this paper · explained in 4 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Longitudinal Data — 1× in this paper · explained in 2 episodes
• Population Synthesis — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

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