Charu Aggarwal

Graph Convolutional Network,Graph Neural Networks,Dynamic Graph,Graph Data,Graph Learning,Node Classification,Representation Learning,Catastrophic Forgetting,Feature Space,Graph Attention Network,Graph Features,Graph Neural Network Model,Graph-structured Data,Incremental Learning,Learning Models,Link Prediction,Low-dimensional Vector,Macro F1 Score,Matrix Factorization,Network Embedding,Node Feature Vectors,Node Information,Nodes In The Graph,Recommender Systems,Self-supervised Learning,Structural Information,Adversarial Attacks,Adversarial Perturbations,Architecture Approach,Attack Methods,Attack Performance,Attack Success,Attack Success Rate,Attack Target,Autoencoder,Automatic Feature Selection,Ball Model,Baseline Methods,Betweenness Centrality,Bias Parameter,Central Node,Centrality Measures,Citation Network,Consolidation Of Knowledge,Correlation-based Feature Selection,Current Graph,Current Time Step,Data Augmentation,Data Augmentation Methods,Deep Learning,