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Found 7 papers, 4 papers with code
Quantifying Node-based Core Resilience
We first show that a previously proposed measure, Core Strength, does not correctly capture the core resilience of a node upon edge removals.
On Measuring the Diversity of Organizational Networks
The interaction patterns of employees in social and professional networks play an important role in the success of employees and organizations as a whole.
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM
Memristor-based weight pruning and weight quantization have been seperately investigated and proven effectiveness in reducing area and power consumption compared to the original DNN model.
Predicting Graph Categories from Structural Properties
Even though the current version of this paper is withdrawn, there was no disagreement between authors on the novel work in this paper.
Network Classification and Categorization
To the best of our knowledge, this paper presents the first large-scale study that tests whether network categories (e. g., social networks vs. web graphs) are distinguishable from one another (using both categories of real-world networks and synthetic graphs).
Hidden Community Detection in Social Networks
We introduce a new paradigm that is important for community detection in the realm of network analysis.
Revealing Multiple Layers of Hidden Community Structure in Networks
Additionally, on both real and synthetic networks containing a hidden ground-truth community structure, HICODE uncovers this structure better than any baseline algorithms that we compared against.
Social and Information Networks Physics and Society
