Ronen Talmon
11 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
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ICML (3)
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Keywords
manifold learning
(3)
riemannian geometry
(2)
graph embedding
(2)
langevin dynamics
(1)
metric learning
(1)
image synthesis
(1)
stochastic gradient descent
(1)
signal separation
(1)
independent component analysis
(1)
parameter estimation
(1)
feature selection
(1)
universal approximation
(1)
statistical independence
(1)
image reconstruction
(1)
neural network optimization
(1)
graph laplacian
(1)
procrustes analysis
(1)
hierarchical representation
(1)
3d reconstruction
(1)
dimensionality reduction
(1)
Papers
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
CVPR 2025
Supervised and Semi-Supervised Diffusion Maps with Label-Driven Diffusion
ICLR 2025
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
ICLR 2025
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters
NIPS 2024
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank
AAAI 2024
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
ICML 2023
Few-Sample Feature Selection via Feature Manifold Learning
ICML 2023
Discovery of Single Independent Latent Variable
NIPS 2022
Hyperbolic Procrustes Analysis Using Riemannian Geometry
NIPS 2021
Option Discovery in the Absence of Rewards with Manifold Analysis
ICML 2020
Statistical Tomography of Microscopic Life
CVPR 2018