Gayan K. Kulatilleke

According to our database, Gayan K. Kulatilleke authored at least 14 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SCGC : Self-supervised contrastive graph clustering.

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

Neurocomputing, 2025

2024

FlowTransformer: A transformer framework for flow-based network intrusion detection systems.

Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann

Expert Syst. Appl., 2024

A Tiered Quadruplet Network with Patient-Specific Mining and Dynamic Margin for Improved ugly Duckling Lesion Classification.

Nathasha Naranpanawa, H. Peter Soyer, Adam Mothershaw, Gayan K. Kulatilleke, Zongyuan Ge, Brigid Betz-Stablein, Shekhar S. Chandra

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023

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

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

Neurocomputing, December, 2023

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

Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann

Appl. Intell., August, 2023

XG-BoT: An explainable deep graph neural network for botnet detection and forensics.

Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann

Internet Things, July, 2023

Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification.

Nathasha Naranpanawa, H. Peter Soyer, Adam Mothershaw, Gayan K. Kulatilleke, Zongyuan Ge, Brigid Betz-Stablein, Shekhar S. Chandra

CoRR, 2023

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

Mohanad Sarhan, Gayan K. Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022

NBC-Softmax : Darkweb Author fingerprinting and migration tracking.

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

CoRR, 2022

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

Gayan K. Kulatilleke, Sugandika Samarakoon

CoRR, 2022

Credit card fraud detection - Classifier selection strategy.

Gayan K. Kulatilleke

CoRR, 2022

Challenges and Complexities in Machine Learning based Credit Card Fraud Detection.

Gayan K. Kulatilleke

CoRR, 2022

FDGATII: Fast Dynamic Graph Attention with Initial Residual and Identity.

Gayan K. Kulatilleke, Marius Portmann, Ryan K. L. Ko, Shekhar S. Chandra

Proceedings of the AI 2022: Advances in Artificial Intelligence, 2022

2021

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

Gayan K. Kulatilleke, Marius Portmann, Ryan K. L. Ko, Shekhar S. Chandra

CoRR, 2021