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Kubilay Atasu

3 accepted papers

2024

Provably Powerful Graph Neural Networks for Directed Multigraphs

AAAI 2024technical

This paper analyses a set of simple adaptations that transform standard message-passing Graph Neural Networks (GNN) into provably powerful directed multigraph neural networks. The adaptations include multigraph port numbering, ego IDs, and reverse message passing. We prove that the combination of th…

Cited by 25SourcePDFScholar
2023

Realistic Synthetic Financial Transactions for Anti-Money Laundering Models

NeurIPS 2023poster

With the widespread digitization of finance and the increasing popularity of cryptocurrencies, the sophistication of fraud schemes devised by cybercriminals is growing. Money laundering -- the movement of illicit funds to conceal their origins -- can cross bank and national boundaries, producing com…

2019

Linear-Complexity Data-Parallel Earth Mover’s Distance Approximations

ICML 2019oral

The Earth Mover’s Distance (EMD) is a state-of-the art metric for comparing discrete probability distributions, but its high distinguishability comes at a high cost in computational complexity. Even though linear-complexity approximation algorithms have been proposed to improve its scalability, thes…