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Found 3 papers, 3 papers with code
The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology
The devices, which we call causal chambers, are computer-controlled laboratories that allow us to manipulate and measure an array of variables from these physical systems, providing a rich testbed for algorithms from a variety of fields.
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
We leverage this procedure and evaluate the performance of GnIES on synthetic, real, and semi-synthetic data sets.
Active Invariant Causal Prediction: Experiment Selection through Stability
A fundamental difficulty of causal learning is that causal models can generally not be fully identified based on observational data only.
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