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ORCIDPuoya Tabaghi
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2020 – today
- 2024
[c10]Samantha Chen, Puoya Tabaghi, Yusu Wang:
Learning Ultrametric Trees for Optimal Transport Regression. AAAI 2024: 20657-20665- [c9]Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Michaël Defferrard, Elahe Rezaei, Ryan Carey, W. Rhett Davis, Rajeev Jain, Yusu Wang:
DE-HNN: An effective neural model for Circuit Netlist representation. AISTATS 2024: 4258-4266 - [c8]Puoya Tabaghi, Yusu Wang:
Universal Representation of Permutation-Invariant Functions on Vectors and Tensors. ALT 2024: 1134-1187 - [c7]Shayesteh Arasti
, Puoya Tabaghi, Yasamin Tabatabaee, Siavash Mirarab:
Optimal Tree Metric Matching Enables Phylogenomic Branch Length Estimation. RECOMB 2024: 462-465 - [i11]Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Donghyeon Koh, Michaël Defferrard, Elahe Rezaei, Ryan Carey, W. Rhett Davis, Rajeev Jain, Yusu Wang:
DE-HNN: An effective neural model for Circuit Netlist representation. CoRR abs/2404.00477 (2024) - 2023
- [j3]Chao Pan, Eli Chien, Puoya Tabaghi, Jianhao Peng, Olgica Milenkovic:
Provably accurate and scalable linear classifiers in hyperbolic spaces. Knowl. Inf. Syst. 65(4): 1817-1850 (2023) - [i10]Puoya Tabaghi, Michael Khanzadeh, Yusu Wang, Siavash Mirarab:
Principal Component Analysis in Space Forms. CoRR abs/2301.02750 (2023) - [i9]Puoya Tabaghi, Yusu Wang:
Universal Representation of Permutation-Invariant Functions on Vectors and Tensors. CoRR abs/2310.13829 (2023) - 2022
- [c6]Eli Chien, Puoya Tabaghi, Olgica Milenkovic:
HyperAid: Denoising in Hyperbolic Spaces for Tree-fitting and Hierarchical Clustering. KDD 2022: 201-211 - [c5]Yueyu Jiang, Puoya Tabaghi, Siavash Mirarab:
Phylogenetic Placement Problem: A Hyperbolic Embedding Approach. RECOMB-CG 2022: 68-85 - [i8]Chao Pan, Eli Chien, Puoya Tabaghi, Jianhao Peng, Olgica Milenkovic:
Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces. CoRR abs/2203.03730 (2022) - [i7]Eli Chien, Puoya Tabaghi, Olgica Milenkovic:
HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering. CoRR abs/2205.09721 (2022) - [i6]Samantha Chen, Puoya Tabaghi, Yusu Wang:
Learning Ultrametric Trees for Optimal Transport Regression. CoRR abs/2210.12288 (2022) - 2021
- [j2]Puoya Tabaghi, Ivan Dokmanic:
On Procrustes Analysis in Hyperbolic Space. IEEE Signal Process. Lett. 28: 1120-1124 (2021) - [c4]Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic:
Highly Scalable and Provably Accurate Classification in Poincaré Balls. ICDM 2021: 61-70 - [i5]Puoya Tabaghi, Eli Chien, Chao Pan, Olgica Milenkovic:
Linear Classifiers in Mixed Constant Curvature Spaces. CoRR abs/2102.10204 (2021) - [i4]Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic:
Highly Scalable and Provably Accurate Classification in Poincare Balls. CoRR abs/2109.03781 (2021) - 2020
- [j1]Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli:
Kinetic Euclidean Distance Matrices. IEEE Trans. Signal Process. 68: 452-465 (2020) - [c3]Puoya Tabaghi, Ivan Dokmanic:
Hyperbolic Distance Matrices. KDD 2020: 1728-1738 - [i3]Puoya Tabaghi, Ivan Dokmanic:
Hyperbolic Distance Matrices. CoRR abs/2005.08672 (2020) - [i2]Puoya Tabaghi, Ivan Dokmanic:
Geometry of Comparisons. CoRR abs/2006.09858 (2020)
2010 – 2019
- 2019
- [c2]Puoya Tabaghi, Ivan Dokmanic, Martin Vetterli:
On the Move: Localization with Kinetic Euclidean Distance Matrices. ICASSP 2019: 4893-4897 - [i1]Puoya Tabaghi, Maarten V. de Hoop, Ivan Dokmanic:
Learning Schatten-Von Neumann Operators. CoRR abs/1901.10076 (2019) - 2015
- [c1]Puoya Tabaghi, Mahmood R. Azimi-Sadjadi:
Class-preserving manifold learning for detection and classification. IJCNN 2015: 1-6
Coauthor Index
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