Differentiable Causal Discovery for Singular Linear Models under Confounding

arXiv:2601.01368 · cs.LG · Submitted 2026-01-04 · Read on arXiv

cs.LG

Submitted: 2026-01-04

Updated: 2026-09-06

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

Terminology

• Causal Discovery — 20× in this paper · explained in 2 episodes
• Adjacency Matrix — 3× in this paper · explained in 1 episode
• Adversarial Training — 3× in this paper · explained in 1 episode
• Linear Structural Equation Model — 3× in this paper
• F1 Score — 2× in this paper · explained in 3 episodes
• Generative Adversarial Network — 2× in this paper
• Kullback-Leibler (KL) Divergence — 2× in this paper · explained in 3 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Widely Applicable Bayesian Information Criterion — 2× in this paper
• Acyclic Directed Mixed Graphs (ADMGs) — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Hamming Distance — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Structural Hamming Distance — 1× in this paper

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