A dependence detection heuristic in causal induction to handle nonbinary variables
Abstract How humans estimate causality is one of the central questions of cognitive science, and many studies have attempted to model this estimation mechanism. Previous studies indicate that the pARIs model is the most descriptive of human causality estimation among 42 normative and descriptive mod...
Saved in:
| Main Authors: | Kohki Higuchi, Tomohiro Shirakawa, Hiroto Ichino, Tatsuji Takahashi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-91051-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Learning High-Order Features for Fine-Grained Visual Categorization with Causal Inference
by: Yuhang Zhang, et al.
Published: (2025-04-01) -
CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy
by: Zahra Taghados, et al.
Published: (2025-04-01) -
Uncovering causal graphs in air traffic control communication logs for explainable root cause analysis
by: Agneza Krajna, et al.
Published: (2025-07-01) -
Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models
by: Mi Jin Noh, et al.
Published: (2025-01-01) -
Granger causal inference for climate change attribution
by: Mark D Risser, et al.
Published: (2025-01-01)