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Synthetic 5 and Synthetic 10 nodes data sets
The Synthetic 5 and Synthetic 10 nodes data sets are synthetic data sets with 5 and 10 nodes respectively. -
Causal Discovery Using Knowledge-guided Greedy Equivalence Search
Learning causal relationships solely from observational data provides insufficient information about the underlying causal mechanism and the search space of possible causal graphs. -
Tuebingen Dataset
The Tuebingen dataset consists of 99 real-world known cause-effect pairs made available by [12]. -
Cause-Effect Pairs Challenge
The cause-effect pairs from the cause-effect pair challenge consisting of 20k datasets of synthetic pairs of variables labeled as causal, anticausal, confounded, and independent. -
Initial Results for Pairwise Causal Discovery Using Quantitative Information ...
Pairwise Causal Discovery is the task of determining causal, anticausal, confounded or independence relationships from pairs of variables. -
Causal Recurrent Variational Autoencoder for Medical Time Series Generation
Causal recurrent variational autoencoder (CR-VAE) for medical time series generation -
Neuro-Causal Factor Analysis
NCFA models used in this paper are a subfamily of the models known as MeDIL causal models, originally introduced in (Markham and Grosse-Wentrup, 2020). -
Light Tunnel Dataset
The light tunnel dataset is a real-world dataset used for causal discovery in physical systems. -
SimpleQuestion dataset for Wikidata
The dataset used in this paper is a reinforcement learning dataset, specifically the SimpleQuestion dataset, which contains questions answerable using Wikidata as the knowledge...
