Score-Based Learning of Cluster DAGs from Interventions
stat.ML, cs.LG
Submitted: 2026-10-08
Updated: 2026-10-08
Code: https://github.com/tedescoG/coarse
Terminology
Sources
- Approximate Causal Abstraction
- Structural Causal Bottleneck Models
- Visual Causal Feature Learning
- I-FLOP: Fast Learning of Order and Parents from Interventional Data
- Large-Sample Learning of Bayesian Networks is NP-Hard
- Causal Abstraction Learning based on the Semantic Embedding Principle
- Estimating a Causal Order among Groups of Variables in Linear Models
- Distributionally Robust Causal Abstractions
- Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
- Causal inference using the algorithmic Markov condition
- GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables
- Greedy Relaxations of the Sparsest Permutation Algorithm
- Coarsening Causal DAG Models
- Coarsening Linear Non-Gaussian Causal Models with Cycles
- Formally Justifying MDL-based Inference of Cause and Effect
- Causal Abstraction with Soft Interventions
- Standardizing Structural Causal Models
- Causal inference using invariant prediction: identification and confidence intervals
- Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game
- Causal Consistency of Structural Equation Models
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