| Linking bank clients using graph neural networks powered by rich transactional data V Shumovskaia, K Fedyanin, I Sukharev, D Berestnev, M Panov International Journal of Data Science and Analytics 12, 135-145, 2021 | 14 | 2021 |
| Online Graph Learning from Social Interactions V Shumovskaia, K Ntemos, S Vlaski, AH Sayed 2021 55th Asilomar Conference on Signals, Systems, and Computers, 1263-1267, 2021 | 7 | 2021 |
| Linking bank clients using graph neural networks powered by rich transactional data: Extended abstract V Shumovskaia, K Fedyanin, I Sukharev, D Berestnev, M Panov 2020 IEEE 7th International Conference on Data Science and Advanced …, 2020 | 5 | 2020 |
| Explainability and Graph Learning from Social Interactions V Shumovskaia, K Ntemos, S Vlaski, AH Sayed IEEE Transactions on Signal and Information Processing over Networks 8, 946-959, 2022 | 2 | 2022 |
| EWS-GCN: Edge weight-shared graph convolutional network for transactional banking data I Sukharev, V Shumovskaia, K Fedyanin, M Panov, D Berestnev 2020 IEEE International Conference on Data Mining (ICDM), 1268-1273, 2020 | 2 | 2020 |
| Towards hypothesis testing for random graphs with community structure V Shumovskaia, M Panov ИТиС 2018, 135-147, 2018 | 1 | 2018 |
| Discovering Influencers in Opinion Formation over Social Graphs V Shumovskaia, M Kayaalp, M Cemri, AH Sayed arXiv preprint arXiv:2211.13292, 2022 | | 2022 |
| How fair is your graph? Exploring fairness concerns in neuroimaging studies F Ribeiro, V Shumovskaia, T Davies, I Ktena Machine Learning for Healthcare, 2022 | | 2022 |
| Evaluating graph fairness in transductive learning F Ribeiro, V Shumovskaia, T Davies, I Ktena Medical Imaging with Deep Learning, 2022 | | 2022 |
| Reproducibility Summary A Atanov, V Shumovskaia, M Vujasinovic | | |
Maxim PanovTechnology Innovation InstituteVerified email at tii.ae
