Research map / Probabilistic and scientific modeling / Causal discovery
Evaluating Bivariate Causal Statements Based on Mutual Compatibility
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Causality can systematically address the monsters under the bench(marks) (NeurIPS 2026 · similarity 0.87)
- Bivariate Causal Discovery using Bayesian Model Selection (ICML 2024 · similarity 0.87)
- Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation (NeurIPS 2026 · similarity 0.87)
- Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond (ICML 2025 · similarity 0.87)
- Causal learning with the invariance principle (NeurIPS 2026 · similarity 0.86)
- Detecting and Measuring Confounding Using Causal Mechanism Shifts (NeurIPS 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.