Cover Image

Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cabezas, Alberto, Sharrock, Louis, Nemeth, Christopher
Format:	Preprint
Published:	2024
Subjects:	Methodology Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tuning-Free Sampling via Optimization on the Space of Probability Measures
by: Sharrock, Louis, et al.
Published: (2025)

Wasserstein Gradient Flows for Batch Bayesian Optimal Experimental Design
by: Sharrock, Louis
Published: (2026)

Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting
by: Sharrock, Louis, et al.
Published: (2023)

Non-Vacuous Certification of Transport MCMC via Oscillation-Controlled Normalizing Flows
by: Hu, Jun
Published: (2026)

Recursive Maximum Likelihood Estimation for Interacting Particle Systems using Virtual Particles
by: Sharrock, Louis, et al.
Published: (2026)

Hypergraph Generation via Structured Stochastic Diffusion
by: Nemeth, Christopher
Published: (2026)

FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
by: Dong, Yuexiao, et al.
Published: (2026)

RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimation
by: Xie, Yifei, et al.
Published: (2026)

Order-based Structure Learning with Normalizing Flows
by: Kamkari, Hamidreza, et al.
Published: (2023)

Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2025)

Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
by: Dodd, Daniel, et al.
Published: (2024)

GPDFlow: Generative Multivariate Threshold Exceedance Modeling via Normalizing Flows
by: Hu, Chenglei, et al.
Published: (2025)

Efficient Online Learning in Interacting Particle Systems
by: Sharrock, Louis, et al.
Published: (2026)

Probabilistically Plausible Counterfactual Explanations with Normalizing Flows
by: Wielopolski, Patryk, et al.
Published: (2024)

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals
by: Arpogaus, Marcel, et al.
Published: (2025)

Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows
by: Hoang, Nu, et al.
Published: (2024)

Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
by: Zeng, Cheng, et al.
Published: (2025)

Scalable Monte Carlo for Bayesian Learning
by: Fearnhead, Paul, et al.
Published: (2024)

DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
by: Wu, Dongze, et al.
Published: (2025)

Flow-based Distributionally Robust Optimization
by: Xu, Chen, et al.
Published: (2023)

Flow-Based Conformal Predictive Distributions
by: Harris, Trevor
Published: (2026)

$ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2022)

Flexible Selective Inference with Flow-based Transport Maps
by: Liu, Sifan, et al.
Published: (2025)

Scalable Bayesian Inference for Generalized Linear Mixed Models via Stochastic Gradient MCMC
by: Berchuck, Samuel I., et al.
Published: (2024)

Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)

Conditioning Gaussian Processes on Almost Anything
by: Moss, Henry, et al.
Published: (2026)

MCMC with Adaptive Principal-Component Transformation: Rotation-Invariant Universal Samplers for Bayesian Structural System Identification
by: Meng, Xianghao, et al.
Published: (2026)

Causal Flow-based Variational Auto-Encoder for Disentangled Causal Representation Learning
by: Fan, Di, et al.
Published: (2023)

Statistical Inference on Gradient Flows
by: Li, Tongyu, et al.
Published: (2026)

Statistical Properties of Rectified Flow
by: Mena, Gonzalo, et al.
Published: (2025)

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies
by: Huk, David, et al.
Published: (2025)

Marginal Causal Flows for Validation and Inference
by: Manela, Daniel de Vassimon, et al.
Published: (2024)

Conformal Prediction via Transported Beta Laws
by: Ramos, Thiago R., et al.
Published: (2026)

Score Matching With Missing Data
by: Givens, Josh, et al.
Published: (2025)

Matrix Completion via Residual Spectral Matching
by: Chen, Ziyuan, et al.
Published: (2024)

Probabilistic Inversion Modeling of Gas Emissions: A Gradient-Based MCMC Estimation of Gaussian Plume Parameters
by: Newman, Thomas, et al.
Published: (2024)

Score Matching for Truncated Density Estimation on a Manifold
by: Williams, Daniel J., et al.
Published: (2022)

Conformal Calibration of Statistical Confidence Sets
by: Cabezas, Luben M. C., et al.
Published: (2024)

Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
by: Nanavati, Praharsh, et al.
Published: (2025)

CREDO: Epistemic-Aware Conformalized Credal Envelopes for Regression
by: Cabezas, Luben M. C., et al.
Published: (2026)