Gayan K. Kulatilleke

FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity Mapping pdf

Marius Portmann, Shekhar S. Chandra, Gayan K. Kulatilleke, 2021, ArXiv.

SCGC : Self-Supervised Contrastive Graph Clustering

Gayan K. Kulatilleke, S. Chandra, Marius Portmann, 2022, 2204.12656.

SCGC : Self-Supervised Contrastive Graph Clustering

Gayan K. Kulatilleke, S. Chandra, Marius Portmann, 2022, ArXiv.

Credit card fraud detection - Classifier selection strategy

Gayan K. Kulatilleke, 2022, ArXiv.

Challenges and Complexities in Machine Learning based Credit Card Fraud Detection

Gayan K. Kulatilleke, 2022, ArXiv.

NBC-Softmax : Darkweb Author fingerprinting and migration tracking

Gayan K. Kulatilleke, S. Chandra, Marius Portmann, 2022, ArXiv.

Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin

Wai Weng Lo, Gayan K. Kulatilleke, Marius Portmann, 2022, Applied Intelligence.

Efficient block contrastive learning via parameter-free meta-node approximation

Gayan K. Kulatilleke, S. Chandra, Marius Portmann, 2022, Neurocomputing.

DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection

Wai Weng Lo, Gayan K. Kulatilleke, Marius Portmann, 2022, 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW).

FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems

Wai Weng Lo, Gayan K. Kulatilleke, Marius Portmann, 2023, Expert Syst. Appl..

Empirical study of Machine Learning Classifier Evaluation Metrics behavior in Massively Imbalanced and Noisy data

Gayan K. Kulatilleke, Sugandika Samarakoon, 2022, ArXiv.