Cover Image

Low Stein Discrepancy via Message-Passing Monte Carlo

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kirk, Nathan, Rusch, T. Konstantin, Zech, Jakob, Rus, Daniela
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Message-Passing Monte Carlo: Generating low-discrepancy point sets via Graph Neural Networks
by: Rusch, T. Konstantin, et al.
Published: (2024)

Neural Low-Discrepancy Sequences
by: Van Huffel, Michael Etienne, et al.
Published: (2025)

Optimizing Kernel Discrepancies via Subset Selection
by: Chen, Deyao, et al.
Published: (2025)

A Bayesian Approach to Low-Discrepancy Subset Selection
by: Kirk, Nathan
Published: (2026)

Neural and spectral operator surrogates: unified construction and expression rate bounds
by: Herrmann, Lukas, et al.
Published: (2022)

On the mean-field limit for Stein variational gradient descent: stability and multilevel approximation
by: Weissmann, Simon, et al.
Published: (2024)

Message-Passing GNNs Fail to Approximate Sparse Triangular Factorizations
by: Trifonov, Vladislav, et al.
Published: (2025)

High-Dimensional Quasi-Monte Carlo via Combinatorial Discrepancy
by: Chen, Jiaheng, et al.
Published: (2025)

Constrained Ensemble Langevin Monte Carlo
by: Ding, Zhiyan, et al.
Published: (2021)

On the optimization of discrepancy measures
by: Clément, François, et al.
Published: (2025)

Transport Quasi-Monte Carlo
by: Liu, Sifan
Published: (2024)

Multi-Level Monte Carlo Training of Neural Operators
by: Rowbottom, James, et al.
Published: (2025)

Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
by: Zhang, Rui, et al.
Published: (2023)

Stein's method for marginals on large graphical models
by: Cui, Tiangang, et al.
Published: (2024)

An improved Halton sequence for implementation in quasi-Monte Carlo methods
by: Kirk, Nathan, et al.
Published: (2024)

Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo
by: Chahine, Makram, et al.
Published: (2024)

Learned Discrepancy Reconstruction and Benchmark Dataset for Magnetic Particle Imaging
by: Iske, Meira, et al.
Published: (2025)

Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension
by: Dong, Yijun, et al.
Published: (2025)

Accelerating Multilevel Markov Chain Monte Carlo Using Machine Learning Models
by: Reddy, Sohail, et al.
Published: (2024)

Oscillatory State-Space Models
by: Rusch, T. Konstantin, et al.
Published: (2024)

Monte Carlo-Type Neural Operator for Differential Equations
by: Choutri, Salah Eddine, et al.
Published: (2025)

When Langevin Monte Carlo Meets Randomization: New Sampling Algorithms with Non-asymptotic Error Bounds beyond Log-Concavity and Gradient Lipschitzness
by: Wang, Xiaojie, et al.
Published: (2025)

Stein transport for Bayesian inference
by: Nüsken, Nikolas
Published: (2024)

Regularized Stein Variational Gradient Flow
by: He, Ye, et al.
Published: (2022)

Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
by: Shao, Zihan, et al.
Published: (2025)

Sparse RBF Networks for PDEs and nonlocal equations: function space theory, operator calculus, and training algorithms
by: Shao, Zihan, et al.
Published: (2026)

Nonuniform random feature models using derivative information
by: Pieper, Konstantin, et al.
Published: (2024)

Quantum speedup of non-linear Monte Carlo problems
by: Blanchet, Jose, et al.
Published: (2025)

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

From Monte Carlo to neural networks approximations of boundary value problems
by: Beznea, Lucian, et al.
Published: (2022)

Operator SVD with Neural Networks via Nested Low-Rank Approximation
by: Ryu, J. Jon, et al.
Published: (2024)

Low-Pass Flow Matching
by: Ruscio, Francesco M., et al.
Published: (2026)

Quasi-Monte Carlo Methods: What, Why, and How?
by: Hickernell, Fred J., et al.
Published: (2025)

Learning to Dissipate Energy in Oscillatory State-Space Models
by: Boyer, Jared, et al.
Published: (2025)

Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
by: Kim, Kyurae, et al.
Published: (2025)

Bit-Accurate Modeling of GPU Matrix Multiply-Accumulate Units: Demystifying Numerical Discrepancy and Accuracy
by: Xie, Peichen, et al.
Published: (2025)

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

Simultaneous Approximation of the Score Function and Its Derivatives by Deep Neural Networks
by: Yakovlev, Konstantin, et al.
Published: (2025)

Adaptive Proximal Gradient Method for Convex Optimization
by: Malitsky, Yura, et al.
Published: (2023)

Sketching Low-Rank Plus Diagonal Matrices
by: Fernandez, Andres, et al.
Published: (2025)