A new deep hierarchical knowledge loss (DHK) with tree and triplet components improves fault intensity diagnosis by modeling class hierarchies on industrial datasets.
InProceedings of the 30th ACM SIGKDD Conference on Knowl- edge Discovery and Data Mining
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Deep Hierarchical Knowledge Loss for Fault Intensity Diagnosis
A new deep hierarchical knowledge loss (DHK) with tree and triplet components improves fault intensity diagnosis by modeling class hierarchies on industrial datasets.