Tran Gia Bao Ngo

According to our database, Tran Gia Bao Ngo authored at least 7 papers between 2024 and 2026.

Collaborative distances:

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

2026

Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation.

Tran Gia Bao Ngo, Md. Zulfikar Alom, Federico Errica, Murat Kantarcioglu, Cuneyt Gurcan Akcora

CoRR, May, 2026

Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection.

Kunal Mukherjee, Md. Zulfikar Alom, Tran Gia Bao Ngo, Cuneyt Gurcan Akcora, Murat Kantarcioglu

CoRR, February, 2026

2025

TGM: a Modular and Efficient Library for Machine Learning on Temporal Graphs.

Jacob Chmura, Shenyang Huang, Tran Gia Bao Ngo, Ali Parviz, Farimah Poursafaei, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany

CoRR, October, 2025

MiNT: Multi-Network Transfer Benchmark for Temporal Graph Learning.

Kiarash Shamsi, Tran Gia Bao Ngo, Razieh Shirzadkhani, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning.

Md. Zulfikar Alom, Tran Gia Bao Ngo, Murat Kantarcioglu, Cuneyt Gurcan Akcora

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Towards Neural Scaling Laws for Foundation Models on Temporal Graphs.

Razieh Shirzadkhani, Tran Gia Bao Ngo, Kiarash Shamsi, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora

CoRR, 2024

GraphPulse: Topological representations for temporal graph property prediction.

Kiarash Shamsi, Farimah Poursafaei, Shenyang Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Gurcan Akcora

Proceedings of the Twelfth International Conference on Learning Representations, 2024