Cover Image

Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Williams, Bernardo, Yu, Hanlin, Luu, Hoang Phuc Hau, Arvanitidis, Georgios, Klami, Arto
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)

Non-geodesically-convex optimization in the Wasserstein space
by: Luu, Hoang Phuc Hau, et al.
Published: (2024)

Learning Geometry and Topology via Multi-Chart Flows
by: Yu, Hanlin, et al.
Published: (2025)

Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics
by: Yu, Hanlin, et al.
Published: (2023)

Riemannian Laplace Approximation with the Fisher Metric
by: Yu, Hanlin, et al.
Published: (2023)

Warped geometric information on the optimisation of Euclidean functions
by: Hartmann, Marcelo, et al.
Published: (2023)

Connecting Neural Models Latent Geometries with Relative Geodesic Representations
by: Yu, Hanlin, et al.
Published: (2025)

Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process
by: Williams, Bernardo, et al.
Published: (2026)

Density Ratio Estimation with Conditional Probability Paths
by: Yu, Hanlin, et al.
Published: (2025)

Simplex-to-Euclidean Bijections for Categorical Flow Matching
by: Williams, Bernardo, et al.
Published: (2025)

Geometric Moment Alignment for Domain Adaptation via Siegel Embeddings
by: Gharib, Shayan, et al.
Published: (2025)

Score-Based Density Estimation from Pairwise Comparisons
by: Mikkola, Petrus, et al.
Published: (2025)

Preferential Normalizing Flows
by: Mikkola, Petrus, et al.
Published: (2024)

Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction
by: Patron, Anri, et al.
Published: (2024)

Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences
by: Yu, Hanlin, et al.
Published: (2026)

Point-Identification of a Robust Predictor Under Latent Shift with Imperfect Proxies
by: Rahiminasab, Zahra, et al.
Published: (2026)

Monge SAM: Robust Reparameterization-Invariant Sharpness-Aware Minimization Based on Loss Geometry
by: Jacobsen, Albert Kjøller, et al.
Published: (2025)

GRADSTOP: Early Stopping of Gradient Descent via Posterior Sampling
by: Jamshidi, Arash, et al.
Published: (2025)

Counterfactual Explanations via Riemannian Latent Space Traversal
by: Pegios, Paraskevas, et al.
Published: (2024)

Staying on the Manifold: Geometry-Aware Noise Injection
by: Jacobsen, Albert Kjøller, et al.
Published: (2025)

On the Identifiability of Tensor Ranks via Prior Predictive Matching
by: da Silva, Eliezer, et al.
Published: (2025)

Amortized Optimal Transport from Sliced Potentials
by: Truong, Minh-Phuc, et al.
Published: (2026)

Don't Stop Me Yet: Sampling Loss Minima via Dissipative Riemannian Mechanics
by: Jacobsen, Albert Kjøller, et al.
Published: (2026)

Extended Neural Contractive Dynamical Systems: On Multiple Tasks and Riemannian Safety Regions
by: Mohammadi, Hadi Beik, et al.
Published: (2024)

Consecutive Preferential Bayesian Optimization
by: Erarslan, Aras, et al.
Published: (2025)

Diffusion-PINN Sampler
by: Shi, Zhekun, et al.
Published: (2024)

One-Step Sampler for Boltzmann Distributions via Drifting
by: Cao, Wenhan, et al.
Published: (2026)

Curvature-Aware PCA with Geodesic Tangent Space Aggregation for Semi-Supervised Learning
by: Levada, Alexandre L. M.
Published: (2026)

Neural Contractive Dynamical Systems
by: Beik-Mohammadi, Hadi, et al.
Published: (2024)

Reducing Memorisation in Generative Models via Riemannian Bayesian Inference
by: Gegenfurtner, Johanna Marie, et al.
Published: (2026)

Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
by: Tang, Luhan, et al.
Published: (2026)

Optimizing Multi-Stage Language Models for Effective Text Retrieval
by: Trung, Quang Hoang, et al.
Published: (2024)

Swift Sampler: Efficient Learning of Sampler by 10 Parameters
by: Yao, Jiawei, et al.
Published: (2024)

Don't Read Everything: A Curvature-Conditioned Query for Linear Attention
by: Le, Dong, et al.
Published: (2026)

Convergence Rates for Distribution Matching with Sliced Optimal Transport
by: Thurin, Gauthier, et al.
Published: (2026)

Multivariate Distributional Reinforcement Learning Using Sliced Divergences
by: Debes, Baptiste, et al.
Published: (2026)

Gradient Flow Sampler-based Distributionally Robust Optimization
by: Xu, Zusen, et al.
Published: (2025)

Curvature-Aware Captioning:Leveraging Geodesic Attention for 3D Scene Understanding
by: He, Ziyao, et al.
Published: (2026)

Progressive Tempering Sampler with Diffusion
by: Rissanen, Severi, et al.
Published: (2025)

Spherical Tree-Sliced Wasserstein Distance
by: Tran, Viet-Hoang, et al.
Published: (2025)