Cover Image

Adaptive Independent Sticky MCMC algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Martino, L., Casarin, R., Leisen, F., Luengo, D.
Format:	Preprint
Published:	2013
Subjects:	Computation Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2024)

Harnessing the Power of Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2025)

Non-Asymptotic Analysis of (Sticky) Track-and-Stop
by: Poiani, Riccardo, et al.
Published: (2025)

High-dimensional Adaptive MCMC with Reduced Computational Complexity
by: Hird, Max, et al.
Published: (2026)

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

On Cyclical MCMC Sampling
by: Wang, Liwei, et al.
Published: (2024)

Conformalized Super Learner
by: Wu, Zhanli, et al.
Published: (2026)

Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals
by: Curbelo, E., et al.
Published: (2025)

MCMC-driven learning
by: Bouchard-Côté, Alexandre, et al.
Published: (2024)

AutoStep: Locally adaptive involutive MCMC
by: Liu, Tiange, et al.
Published: (2024)

Diffusion Generative Modelling for Divide-and-Conquer MCMC
by: Trojan, C., et al.
Published: (2024)

Policy Gradients for Optimal Parallel Tempering MCMC
by: Zhao, Daniel, et al.
Published: (2024)

Stochastic Approximation with Biased MCMC for Expectation Maximization
by: Gruffaz, Samuel, et al.
Published: (2024)

Conformalized Regression for Continuous Bounded Outcomes
by: Wu, Zhanli, et al.
Published: (2025)

Comparison of parallel SMC and MCMC for Bayesian deep learning
by: Liang, Xinzhu, et al.
Published: (2024)

PolytopeWalk: Sparse MCMC Sampling over Polytopes
by: Sun, Benny, et al.
Published: (2024)

Efficiently Vectorized MCMC on Modern Accelerators
by: Dance, Hugh, et al.
Published: (2025)

Asymptotically exact variational flows via involutive MCMC kernels
by: Xu, Zuheng, et al.
Published: (2025)

A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
by: Llorente, F., et al.
Published: (2021)

JaxSGMC: Modular stochastic gradient MCMC in JAX
by: Thaler, Stephan, et al.
Published: (2025)

A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
by: Hird, Max, et al.
Published: (2026)

Distributed MCMC inference for Bayesian Non-Parametric Latent Block Model
by: Khoufache, Reda, et al.
Published: (2024)

Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
by: Gonzalez, Emmanuel Anaya, et al.
Published: (2025)

GRASP-GCN: Graph-Shape Prioritization for Neural Architecture Search under Distribution Shifts
by: Casarin, Sofia, et al.
Published: (2024)

A note on the area under the likelihood and the fake evidence for model selection
by: Martino, L., et al.
Published: (2026)

Multi-SpaCE: Multi-Objective Subsequence-based Sparse Counterfactual Explanations for Multivariate Time Series Classification
by: Refoyo, Mario, et al.
Published: (2024)

LLM-Independent Adaptive RAG: Let the Question Speak for Itself
by: Marina, Maria, et al.
Published: (2025)

AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization
by: Bieringer, Sebastian, et al.
Published: (2023)

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

Efficient Sampling on Riemannian Manifolds via Langevin MCMC
by: Cheng, Xiang, et al.
Published: (2024)

Learning to Explore for Stochastic Gradient MCMC
by: Kim, SeungHyun, et al.
Published: (2024)

Bayesian neural networks via MCMC: a Python-based tutorial
by: Chandra, Rohitash, et al.
Published: (2023)

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

Learning Multimodal Latent Space with EBM Prior and MCMC Inference
by: Yuan, Shiyu, et al.
Published: (2024)

Particle-MALA and Particle-mGRAD: Gradient-based MCMC methods for high-dimensional state-space models
by: Corenflos, Adrien, et al.
Published: (2024)

Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems
by: Corenflos, Adrien, et al.
Published: (2023)

Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusion
by: Casarin, Sofia, et al.
Published: (2024)

Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems
by: Cao, Lianghao, et al.
Published: (2024)

Metropolis Sampling
by: Martino, Luca, et al.
Published: (2017)

From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling
by: Renaud, Marien, et al.
Published: (2025)