A new perspective on" how graph neural networks go beyond weisfeiler-lehman?" A Wijesinghe, Q Wang The Tenth International Conference on Learning Representations (ICLR 2022), 2022 | 103 | 2022 |
DFNets: Spectral CNNs for graphs with feedback-looped filters A Wijesinghe, Q Wang Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), 2019 | 31 | 2019 |
-WL: A New Hierarchy of Expressivity for Graph Neural Networks Q Wang, DZ Chen, A Wijesinghe, S Li, M Farhan The Eleventh International Conference on Learning Representations (ICLR 2023), 2023 | 11 | 2023 |
ERGAN: Generative Adversarial Networks for Entity Resolution J Shao, Q Wang, A Wijesinghe, E Rahm Twentieth IEEE International Conference on Data Mining (ICDM 2020), 2020 | 7 | 2020 |
A Regularized Wasserstein Framework for Graph Kernels A Wijesinghe, Q Wang, S Gould Twenty-first IEEE International Conference on Data Mining (ICDM 2021), 2021 | 5 | 2021 |
Autogenous diabetic retinopathy censor for ophthalmologists-AKSHI A Wijesinghe, ND Kodikara, D Sandaruwan IEEE International Conference on Control and Robotics Engineering (ICCRE …, 2016 | 5 | 2016 |
Speed up Robust Features in Computer Vision Systems A Wijesinghe | 2 | 2014 |
Machine Learning Based Approach for Disease Diagnosis of Human Retina A Wijesinghe, ND Kodikara, MKD Sandaruwan | 1 | 2015 |
Geometric Learning on Graph Structured Data A Wijesinghe | | 2022 |