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I am a postdoctoral researcher at Technical University of Munich advised by Prof. Stefanie Jegelka and affiliated with the Munich Center for Machine Learning. Previously, I received my PhD in the Electrical and Computer Engineering Faculty at the Technion under the supervision of Prof. Ronen Talmon.
My research interests are geometric learning and graph machine learning.
Publications
Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
NeurIPS, 2025
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Thomas Dagès*, Simon Weber*, Ya-Wei Eileen Lin, Ronen Talmon, Daniel Cremers, Michael Lindenbaum, Alfred M. Bruckstein, Ron Kimmel
CVPR, 2025
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
ICLR, 2025
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters
Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie
NeurIPS, 2024
Hyperbolic Distance Based on EMD and Diffusion for Hyperspectral Imaging
Hyperbolic Distance Based on EMD and Diffusion for Hyperspectral Imaging
Elad Lavi, Amir Bourvine, Ya-Wei Eileen Lin, Ronen Talmon
ICASSP, 2025
The Tumor Microenvironment of Non–Small Cell Lung Cancer Impairs Immune Cell Function in People with HIV
The Tumor Microenvironment of Non–Small Cell Lung Cancer Impairs Immune Cell Function in People with HIV
Shruti S Desai, Syim Salahuddin, Ramsey Yusuf, Kishu Ranjan, Jianlei Gu, Lais Osmani, Ya-Wei Eileen Lin, Sameet Mehta, Ronan Talmon, Insoo Kang, Yuval Kluger, Hongyu Zhao, Kurt Schalper, Brinda Emu
The Journal of Clinical Investigation, 2025
Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets
Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets
Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon
ICASSP, 2024
Spatial Analysis Reveals Impaired Immune Cell Function within the Tumor Microenvironment of HIV-Associated Non-Small Cell Lung Cancer
Spatial Analysis Reveals Impaired Immune Cell Function within the Tumor Microenvironment of HIV-Associated Non-Small Cell Lung Cancer
Shruti Desai, Syim Salahuddin, Ramsey Yusuf, Kishu Ranjan, Jianlei Gu, Ya-Wei Eileen Lin, Ronan Talmon, Yuval Kluger, Hongyu Zhao, Kurt Schalper, Brinda Emu
medRxiv, 2023
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon
ICML, 2023
Hyperbolic Procrustes Analysis Using Riemannian Geometry
Hyperbolic Procrustes Analysis Using Riemannian Geometry
Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon
NeurIPS, 2021
Graph of Graphs Analysis for Multiplexed Data with Application to Imaging Mass Cytometry
Graph of Graphs Analysis for Multiplexed Data with Application to Imaging Mass Cytometry
Ya-Wei Eileen Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt Schalper, Yuval Kluger
PLoS computational biology, 2021
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