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Found 3 papers, 1 papers with code
Stable and Interpretable Deep Learning for Tabular Data: Introducing InterpreTabNet with the Novel InterpreStability Metric
The proposed model and metric mark a significant stride forward in explainable models' research, setting a standard for transparency and interpretability in AI model design and application across diverse sectors.
Transfer Learning from Synthetic In-vitro Soybean Pods Dataset for In-situ Segmentation of On-branch Soybean Pod
In the first step, we finetune an instance segmentation network pretrained by a source domain (MS COCO dataset) with a synthetic target domain (in-vitro soybean pods dataset).
A Survey of Knowledge Tracing: Models, Variants, and Applications
We hope that the current survey will assist both researchers and practitioners in fostering the development of KT, thereby benefiting a broader range of students.
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