Cover Image

Information Theoretic Bayesian Optimization over the Probability Simplex

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pavesi, Federico, Candelieri, Antonio, Jaquier, Noémie
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Weighted Wasserstein Barycenter of Gaussian Processes for exotic Bayesian Optimization tasks
by: Candelieri, Antonio, et al.
Published: (2026)

Wasserstein Barycenter Gaussian Process based Bayesian Optimization
by: Candelieri, Antonio, et al.
Published: (2025)

Unraveling the Single Tangent Space Fallacy: An Analysis and Clarification for Applying Riemannian Geometry in Robot Learning
by: Jaquier, Noémie, et al.
Published: (2023)

Transformers for Tabular Data: A Training Perspective of Self-Attention via Optimal Transport
by: Quadrio, Alessandro, et al.
Published: (2025)

Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
by: Friedl, Katharina, et al.
Published: (2025)

On Probabilistic Pullback Metrics for Latent Hyperbolic Manifolds
by: Augenstein, Luis, et al.
Published: (2024)

Riemannian Flow Matching Policy for Robot Motion Learning
by: Braun, Max, et al.
Published: (2024)

Fast and Robust Visuomotor Riemannian Flow Matching Policy
by: Ding, Haoran, et al.
Published: (2024)

Taxonomy-aware Dynamic Motion Generation on Hyperbolic Manifolds
by: Augenstein, Luis, et al.
Published: (2025)

Riemann$^2$: Learning Riemannian Submanifolds from Riemannian Data
by: Rozo, Leonel, et al.
Published: (2025)

A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
by: Friedl, Katharina, et al.
Published: (2024)

Information-Theoretic Bayesian Optimization for Bilevel Optimization Problems
by: Kanayama, Takuya, et al.
Published: (2025)

Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
by: Esaki, Yasushi, et al.
Published: (2024)

Information-Theoretic Safe Bayesian Optimization
by: Bottero, Alessandro G., et al.
Published: (2024)

Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds
by: Jaquier, Noémie, et al.
Published: (2022)

Label Distribution Learning using the Squared Neural Family on the Probability Simplex
by: Zhang, Daokun, et al.
Published: (2024)

Gromov-Wasserstein and optimal transport: from assignment problems to probabilistic numeric
by: Seyedi, Iman, et al.
Published: (2025)

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization
by: Wang, Hao, et al.
Published: (2022)

Wasserstein-enabled characterization of designs and myopic decisions in Bayesian Optimization
by: Candelieri, Antonio, et al.
Published: (2026)

Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
by: Nguyen, Khoa, et al.
Published: (2025)

Optimal Transport-based Permutation-Invariant Bayesian Optimization of Offshore Wind Farm Layouts
by: Candelieri, Antonio, et al.
Published: (2026)

Decoding as Optimisation on the Probability Simplex: From Top-K to Top-P (Nucleus) to Best-of-K Samplers
by: Ji, Xiaotong, et al.
Published: (2026)

Information-Theoretic Perspectives on Optimizers
by: Tan, Zhiquan, et al.
Published: (2025)

A Bayesian Information-Theoretic Approach to Data Attribution
by: Tailor, Dharmesh, et al.
Published: (2026)

AlphaFold's Bayesian Roots in Probability Kinematics
by: Hamelryck, Thomas, et al.
Published: (2025)

Bayesian Optimization of Functions over Node Subsets in Graphs
by: Liang, Huidong, et al.
Published: (2024)

Simplex Deep Linear Discriminant Analysis
by: Tezekbayev, Maxat, et al.
Published: (2026)

Transfer Learning in Robotics: An Upcoming Breakthrough? A Review of Promises and Challenges
by: Jaquier, Noémie, et al.
Published: (2023)

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs
by: Mostowsky, Peter, et al.
Published: (2024)

Bayesian Optimization over Bounded Domains with the Beta Product Kernel
by: Nguyen, Huy Hoang, et al.
Published: (2025)

BITS for GAPS: Bayesian Information-Theoretic Sampling for hierarchical GAussian Process Surrogates
by: Jones, Kyla D., et al.
Published: (2025)

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

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
by: Sucker, Michael, et al.
Published: (2024)

Big Batch Bayesian Active Learning by Considering Predictive Probabilities
by: Ober, Sebastian W., et al.
Published: (2025)

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex
by: Qu, Yun, et al.
Published: (2026)

Ranking over Regression for Bayesian Optimization and Molecule Selection
by: Tom, Gary, et al.
Published: (2024)

Robust Multi-Manifold Clustering via Simplex Paths
by: Chen, Haoyu, et al.
Published: (2025)

The Multiclass Score-Oriented Loss (MultiSOL) on the Simplex
by: Marchetti, Francesco, et al.
Published: (2025)

Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization
by: Abdolali, Maryam, et al.
Published: (2024)

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