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2020 – today
- 2025
[c7]Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin, Ronen Talmon, Daniel Cremers, Michael Lindenbaum, Alfred M. Bruckstein, Ron Kimmel:
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding. CVPR 2025: 25842-25853- [c6]Elad Lavi, Amir Bourvine, Ya-Wei Eileen Lin, Ronen Talmon:
Hyperbolic Distance Based on EMD and Diffusion for Hyperspectral Imaging. ICASSP 2025: 1-5 - [c5]Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon:
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy. ICLR 2025 - [i6]Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon:
Coupled Hierarchical Structure Learning using Tree-Wasserstein Distance. CoRR abs/2501.03627 (2025) - [i5]Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin, Ronen Talmon, Daniel Cremers, Michael Lindenbaum, Alfred M. Bruckstein, Ron Kimmel:
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding. CoRR abs/2503.18010 (2025) - [i4]Ya-Wei Eileen Lin, Ron Levie:
Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks. CoRR abs/2509.24886 (2025) - 2024
- [c4]Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon:
Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets. ICASSP 2024: 6325-6329 - [c3]Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie:
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters. NeurIPS 2024 - [i3]Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie:
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters. CoRR abs/2406.01249 (2024) - [i2]Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon:
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy. CoRR abs/2410.21107 (2024) - 2023
- [c2]Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne
, Ronen Talmon:
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning. ICML 2023: 21003-21025 - [i1]Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon:
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning. CoRR abs/2305.18962 (2023) - 2021
- [j1]Ya-Wei Eileen Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt A. Schalper, Yuval Kluger:
Graph of graphs analysis for multiplexed data with application to imaging mass cytometry. PLoS Comput. Biol. 17(3) (2021) - [c1]Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon:
Hyperbolic Procrustes Analysis Using Riemannian Geometry. NeurIPS 2021: 5959-5971
Coauthor Index
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