:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gautier, Guillaume, Bardenet, Rémi, Valko, Michal
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Statistics Theory
Online Access:	https://arxiv.org/abs/2604.19698
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Monte Carlo and quasi-Monte Carlo integration for likelihood functions
by: Tang, Yanbo
Published: (2025)

Duality induced by an embedding structure of determinantal point process
by: Hino, Hideitsu, et al.
Published: (2024)

Weighted least-squares approximation with determinantal point processes and generalized volume sampling
by: Nouy, Anthony, et al.
Published: (2023)

Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance
by: Petrovic, Vladimir, et al.
Published: (2025)

Signal reconstruction using determinantal sampling
by: Belhadji, Ayoub, et al.
Published: (2023)

Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning
by: Grill, Jean-Bastien, et al.
Published: (2026)

Quenched large deviations for Monte Carlo integration with Coulomb gases
by: Bardenet, Rémi, et al.
Published: (2025)

Improved Guarantees for Langevin Monte Carlo with Average Smoothness
by: Dalalyan, Arnak S., et al.
Published: (2026)

Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition
by: Lee, Holden, et al.
Published: (2024)

Covariance estimation using Markov chain Monte Carlo
by: Kook, Yunbum, et al.
Published: (2024)

Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev
by: Chewi, Sinho, et al.
Published: (2021)

Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
by: Ghosh, Soumyadip, et al.
Published: (2021)

Sampling conditioned diffusions via Pathspace Projected Monte Carlo
by: Grafke, Tobias
Published: (2025)

Parallelized Midpoint Randomization for Langevin Monte Carlo
by: Yu, Lu, et al.
Published: (2024)

Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)

GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
by: Bou-Rabee, Nawaf, et al.
Published: (2024)

Deep spatio-temporal point processes: Advances and new directions
by: Cheng, Xiuyuan, et al.
Published: (2025)

Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
by: Guo, Wei, et al.
Published: (2024)

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
by: Miranda, Charles, et al.
Published: (2023)

Handling Covariate Mismatch in Federated Linear Prediction
by: Ayme, Alexis, et al.
Published: (2026)

Complexity of Markov Chain Monte Carlo for Generalized Linear Models
by: Chak, Martin, et al.
Published: (2025)

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
by: Dalalyan, Arnak S., et al.
Published: (2017)

Convergence of Kinetic Langevin Monte Carlo on Lie groups
by: Kong, Lingkai, et al.
Published: (2024)

Non-asymptotic estimates for accelerated high order Langevin Monte Carlo algorithms
by: Neufeld, Ariel, et al.
Published: (2024)

Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis
by: Khellaf, Rémi, et al.
Published: (2024)

Random features models: a way to study the success of naive imputation
by: Ayme, Alexis, et al.
Published: (2024)

Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
by: De Castro, Yohann, et al.
Published: (2025)

On the convergence of dynamic implementations of Hamiltonian Monte Carlo and No U-Turn Samplers
by: Durmus, Alain, et al.
Published: (2023)

A path-norm toolkit for modern networks: consequences, promises and challenges
by: Gonon, Antoine, et al.
Published: (2023)

Algorithmic warm starts for Hamiltonian Monte Carlo
by: Zhang, Matthew S., et al.
Published: (2026)

Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings
by: Bou-Rabee, Nawaf, et al.
Published: (2026)

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
by: You, Kisung
Published: (2026)

Non-asymptotic analysis of Langevin-type Monte Carlo algorithms
by: Nakakita, Shogo
Published: (2023)

Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding
by: Rouault, Martin, et al.
Published: (2024)

Repelling-Attracting Hamiltonian Monte Carlo
by: Vishwanath, Siddharth, et al.
Published: (2024)

An Equivalence between Bayesian Priors and Penalties in Variational Inference
by: Wolinski, Pierre, et al.
Published: (2020)

Seeded graph matching for the correlated Gaussian Wigner model via the projected power method
by: Araya, Ernesto, et al.
Published: (2022)

On determinantal point processes with nonsymmetric kernels
by: Arnaud, Poinas
Published: (2024)

Point processes with event time uncertainty
by: Cheng, Xiuyuan, et al.
Published: (2024)

Adaptive sparse variational approximations for Gaussian process regression
by: Nieman, Dennis, et al.
Published: (2025)