Scholar
Samantha Chen
Google Scholar ID: W_tx4c0AAAAJ
University of California - San Diego
Citations & Impact
Citations
71
H-index
5
i10-index
3
Publications
6
Co-authors
0
Contact
Publications
Resume
Academic Achievements
- De-Coupled NeuroGF for Shortest Path Distance Approximations on Large Terrains (ICML 2025)
- Graph neural networks extrapolate out-of-distribution for shortest paths (preprint 2025)
- Neural approximations of Wasserstein distance via a universal architecture for symmetric and factor-wise group invariant functions (NeurIPS 2023)
- Learning Ultrametric Trees for Optimal Transport Regression (AAAI 2024)
- The Weisfeiler-Lehman Distance: Reinterpretation and Connection GNNs (ICML workshop 2023)
- Weisfeiler-Lehman meets Gromov-Wasserstein (ICML 2022)
- Approximation algorithms for 1-Wasserstein distance between persistence diagrams (SEA 2021)
Research Experience
- Currently working on research related to optimal transport, neural networks, geometric deep learning, and geometric algorithms/problems.
Education
- Started PhD at UCSD in Fall 2020, undergraduate degree in computer science and math from Carleton College. Advisor is Yusu Wang.
Background
- PhD student in the CSE department at UCSD, with research interests in optimal transport, neural networks, geometric deep learning, and geometric algorithms/problems.
Miscellany
- Based in San Diego, follow her on Twitter and GitHub.