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Found 4 papers, 1 papers with code
Experimental design for causal query estimation in partially observed biomolecular networks
Therefore, designing an experiment based on a well-chosen subset of network components can increase estimation accuracy, and reduce experimental and computational costs.
Do-calculus enables estimation of causal effects in partially observed biomolecular pathways
This has limited the use of LVMs for causal inference in biomolecular pathways.
Identifying Aggression and Toxicity in Comments using Capsule Network
As comments tend to be written in more than one language, and transliteration is a common problem, we further show that our model handles this effectively by applying our model on TRAC shared task dataset which contains comments in code-mixed Hindi-English.
Comparative Benchmarking of Causal Discovery Techniques
In this paper we present a comprehensive view of prominent causal discovery algorithms, categorized into two main categories (1) assuming acyclic and no latent variables, and (2) allowing both cycles and latent variables, along with experimental results comparing them from three perspectives: (a) structural accuracy, (b) standard predictive accuracy, and (c) accuracy of counterfactual inference.
