Embedding vs. reconstruction-level contrast (RLC).

<p>Top: the encoder consumes two inputs (the original graph and an augmented view) and contrasts their node embeddings in the embedding space. Bottom: DCOR uses dual autoencoders to reconstruct the adjacency and the attribute matrices for the original graph and the augmented view, then applies...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Hossein Rafieizadeh (22676722) (author)
مؤلفون آخرون:	Hadi Zare (20073000) (author), Mohsen Ghassemi Parsa (22676725) (author), Hocine Cherifi (8177628) (author)
منشور في:	2025
الموضوعات:	Cell Biology Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified intrusions across social reconstructions across views level contrastive learning dual contrastive learning across six benchmarks div >< p view discrepancies underutilized augmented graph views dcor improves auroc view discrepancies level contrast dual autoencoder augmented view specific information six datasets reduces auroc publicly available preserves fine physical domains performing non maximum gain leaving cross identifying threats financial fraud existing graph dcor reconstructs dcor ), contrasts reconstructions attributed networks attribute patterns
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

Embedding vs. reconstruction-level contrast (RLC).

مواد مشابهة