Heat-passing framework for robust interpretation of data in networks.
Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transform...
Main Authors: | Yi Fang, Mengtian Sun, Karthik Ramani |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2015-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4323200?pdf=render |
Similar Items
-
Global geometric affinity for revealing high fidelity protein interaction network.
by: Yi Fang, et al.
Published: (2011-05-01) -
Sensible Performance Analysis of Multi-Pass Cross Flow Heat Exchangers
by: Silaipillayarputhur Karthik, et al.
Published: (2017-01-01) -
Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
by: Sperber, Matthias, et al.
Published: (2019-11-01) -
The issues in methodology and data interpretation in studies of tourist attractions’ attendance: annual passes
by: Lukáš Nekolný, et al.
Published: (2018-09-01) -
A Message-Passing Interpretation of Adjoint Logic
by: Klaas Pruiksma, et al.
Published: (2019-04-01)