| Kinetic Euclidean distance matrices P Tabaghi, I Dokmanić, M Vetterli IEEE Transactions on Signal Processing 68, 452-465, 2019 | 43 | 2019 |
| Hyperbolic distance matrices P Tabaghi, I Dokmanić Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 32 | 2020 |
| Learning hyperbolic embedding for phylogenetic tree placement and updates Y Jiang, P Tabaghi, S Mirarab Biology 11 (9), 1256, 2022 | 15 | 2022 |
| On procrustes analysis in hyperbolic space P Tabaghi, I Dokmanić IEEE Signal Processing Letters 28, 1120-1124, 2021 | 15 | 2021 |
| Highly scalable and provably accurate classification in poincaré balls E Chien, C Pan, P Tabaghi, O Milenkovic 2021 IEEE International Conference on Data Mining (ICDM), 61-70, 2021 | 11 | 2021 |
| Linear classifiers in product space forms P Tabaghi, C Pan, E Chien, J Peng, O Milenkovic arXiv preprint arXiv:2102.10204, 2021 | 9* | 2021 |
| Learning Schatten--von Neumann Operators P Tabaghi, M de Hoop, I Dokmanić arXiv preprint arXiv:1901.10076, 2019 | 8 | 2019 |
| Principal component analysis in space forms P Tabaghi, M Khanzadeh, Y Wang, S Mirarab IEEE Transactions on Signal Processing, 2024 | 7 | 2024 |
| Universal representation of permutation-invariant functions on vectors and tensors P Tabaghi, Y Wang International Conference on Algorithmic Learning Theory, 1134-1187, 2024 | 6 | 2024 |
| Geometry of Similarity Comparisons P Tabaghi, J Peng, O Milenkovic, I Dokmanić arXiv preprint arXiv:2006.09858, 2020 | 6* | 2020 |
| Hyperaid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering E Chien, P Tabaghi, O Milenkovic Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 5 | 2022 |
| DE-HNN: An effective neural model for Circuit Netlist representation Z Luo, TS Hy, P Tabaghi, M Defferrard, E Rezaei, RM Carey, R Davis, ... International Conference on Artificial Intelligence and Statistics, 4258-4266, 2024 | 4 | 2024 |
| Phylogenetic placement problem: A hyperbolic embedding approach Y Jiang, P Tabaghi, S Mirarab RECOMB International Workshop on Comparative Genomics, 68-85, 2022 | 4 | 2022 |
| On the move: Localization with kinetic Euclidean distance matrices P Tabaghi, I Dokmanić, M Vetterli ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 4 | 2019 |
| Learning ultrametric trees for optimal transport regression S Chen, P Tabaghi, Y Wang Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20657 …, 2024 | 3 | 2024 |
| Provably accurate and scalable linear classifiers in hyperbolic spaces C Pan, E Chien, P Tabaghi, J Peng, O Milenkovic Knowledge and Information Systems 65 (4), 1817-1850, 2023 | 3 | 2023 |
| Branch Length Transforms using Optimal Tree Metric Matching S Arasti, P Tabaghi, Y Tabatabaee, S Mirarab bioRxiv, 2023.11. 13.566962, 2023 | 2 | 2023 |
| Real polynomial gram matrices without real spectral factors P Tabaghi, I Dokmanić arXiv preprint arXiv:1903.04085, 2019 | 2 | 2019 |
| Optimal Tree Metric Matching Enables Phylogenomic Branch Length Estimation S Arasti, P Tabaghi, Y Tabatabaee, S Mirarab International Conference on Research in Computational Molecular Biology, 462-465, 2024 | | 2024 |
| Optimal Tree Metric Matching Enables Phylogenomic Branch Length Reconciliation S Arasti, P Tabaghi, Y Tabatabaee, S Mirarab | | 2023 |
Ivan DokmanićAssociate Professor, Department of Mathematics and Computer Science, University of Basel在 illinois.edu 的电子邮件经过验证