Talmon, Ronen

17 publications

CVPR 2025 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

TMLR 2025 Geometric Optimal Transport for Unsupervised Domain Adaptation Gal Maman, Ronen Talmon

NeurIPS 2025 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 Learning Shared Representations from Unpaired Data Amitai Yacobi, Nir Ben-Ari, Ronen Talmon, Uri Shaham

NeurIPS 2025 Spectral Graph Coarsening Using Inner Product Preservation and the Grassmann Manifold Ido Cohen, Ronen Talmon

ICLR 2025 Supervised and Semi-Supervised Diffusion Maps with Label-Driven Diffusion Harel Mendelman, Ronen Talmon

ICLR 2025 Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon

NeurIPS 2024 Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters Ya-Wei Eileen Lin, Ronen Talmon, Ron Levie

TMLR 2024 Supervised Domain Adaptation Based on Marginal and Conditional Distributions Alignment Ori Katz, Ronen Talmon, Uri Shaham

AAAI 2024 The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon

ICML 2023 Few-Sample Feature Selection via Feature Manifold Learning David Cohen, Tal Shnitzer, Yuval Kluger, Ronen Talmon

ICML 2023 Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon

NeurIPS 2022 Discovery of Single Independent Latent Variable Uri Shaham, Jonathan Svirsky, Ori Katz, Ronen Talmon

NeurIPS 2021 Hyperbolic Procrustes Analysis Using Riemannian Geometry Ya-Wei Eileen Lin, Yuval Kluger, Ronen Talmon

ECML-PKDD 2021 Joint Geometric and Topological Analysis of Hierarchical Datasets Lior Aloni, Omer Bobrowski, Ronen Talmon

ICML 2020 Option Discovery in the Absence of Rewards with Manifold Analysis Amitay Bar, Ronen Talmon, Ron Meir

WACV 2019 DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic Sampling Gautam Pai, Ronen Talmon, Alexander M. Bronstein, Ron Kimmel