Get Started
Research questionHow can conditional-distribution asymmetries reveal causal direction in bivariate observational numerical data?Observational association does not by itself determine whether one variable causes the other or the reverse. The difficulty is finding directional information in the joint and conditional distributions of the pair.
Machine Learning
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Identification of Bivariate Causal Directionality Based on Anticipated Asymmetric GeometriesApplies to stochastic bivariate numerical data. The evidence assumes anticipated unimodality in conditional distributions of the effect and evaluates distributional and gradient-based directionality criteria, including hyperparameter tuning, on 99 Tubingen cause-effect pairs; no interventional data or additional variables are specified.research paper · Sep 3, 2026
Related questions
How can complex causal queries be identified under non-IID data, transfer, and missing observations?How can differentiable causal discovery override wrong edge priors while preserving directional identifiability?How can causal explanations scale to individual outcomes without abandoning counterfactual causal structure?How can causal discovery recover causal structures when time series shift across latent regimes?
Home
Topics
Search
Library