8 citations · 9 across the 5 of their papers we have counts for
5 papers
Evaluating Loss Functions for Graph Neural Networks: Towards Pretraining and Generalization
Khushnood Abbas, Ruizhe Hou, Zhou Wengang +4
Graph Neural Networks (GNNs) became useful for learning on non-Euclidean data. However, their best performance depends on choosing the right model architecture and the training obj…
TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix
Khushnood Abbas, Alireza Abbasi, Dong Shi +4
Understanding the evolutionary patterns of real-world evolving complex systems such as human interactions, transport networks, biological interactions, and computer networks has im…
Rising Novelties on Evolving Networks: Recent Behavior Dominant and Non-Dominant Model
Khushnood Abbas
Novelty attracts attention like popularity. Hence predicting novelty is as important as popularity. Novelty is the side effect of competition and aging in evolving systems. Recent…
Identifying emerging influential Nodes in evolving networks: Exploiting strength of weak nodes
Khushnood Abbas, Mingsheng Shang, Cai Shi-Min +1
Identifying emerging influential or popular node/item in future on network is a current interest of the researchers. Most of previous works focus on identifying leaders in time evo…
Discovering items with potential popularity on social media
Khushnood Abbas, Shang Mingsheng, Luo Xin
Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's infl…