3 papers
cs.LG2025
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Hanlin Yu, Berfin Inal, Georgios Arvanitidis +3
Neural models learn representations of high-dimensional data on low-dimensional manifolds. Multiple factors, including stochasticities in the training process, model architectures,…
cs.LG2025
Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature
Bernardo Williams, Hanlin Yu, Hoang Phuc Hau Luu +2
Traditional Markov Chain Monte Carlo sampling methods often struggle with sharp curvatures, intricate geometries, and multimodal distributions. Slice sampling can resolve local exp…
cs.LG2025
Density Ratio Estimation with Conditional Probability Paths
Hanlin Yu, Arto Klami, Aapo Hyvärinen +2
Density ratio estimation in high dimensions can be reframed as integrating a certain quantity, the time score, over probability paths which interpolate between the two densities. I…