Node embeddings and exact low-rank representations of complex networks S Chanpuriya, C Musco, K Sotiropoulos, C Tsourakakis Advances in neural information processing systems 33, 13185-13198, 2020 | 40 | 2020 |
Infinitewalk: Deep network embeddings as laplacian embeddings with a nonlinearity S Chanpuriya, C Musco Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 37 | 2020 |
Simplified graph convolution with heterophily S Chanpuriya, C Musco Advances in Neural Information Processing Systems 35, 27184-27197, 2022 | 21 | 2022 |
On the power of edge independent graph models S Chanpuriya, C Musco, K Sotiropoulos, C Tsourakakis Advances in Neural Information Processing Systems 34, 24418-24429, 2021 | 15 | 2021 |
Deepwalking backwards: from embeddings back to graphs S Chanpuriya, C Musco, K Sotiropoulos, C Tsourakakis International conference on machine learning, 1473-1483, 2021 | 14 | 2021 |
Direct embedding of temporal network edges via time-decayed line graphs S Chanpuriya, RA Rossi, S Kim, T Yu, J Hoffswell, N Lipka, S Guo, ... The Eleventh International Conference on Learning Representations, 2022 | 6 | 2022 |
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings S Chanpuriya, R Rossi, AB Rao, T Mai, N Lipka, Z Song, C Musco Advances in Neural Information Processing Systems 36, 2024 | 1* | 2024 |
On the Role of Edge Dependency in Graph Generative Models S Chanpuriya, CN Musco, K Sotiropoulos, C Tsourakakis | | 2023 |
Latent Random Steps as Relaxations of Max-Cut, Min-Cut, and More S Chanpuriya, C Musco arXiv preprint arXiv:2308.06448, 2023 | | 2023 |
Foundations of Node Representation Learning S Chanpuriya | | 2023 |