High-dimensional Adaptive MCMC with Reduced Computational Complexity
Fuente:
arXiv
Saved in:
| Main Authors: | Hird, Max, Livingstone, Samuel |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
by: Hird, Max, et al.
Published: (2026)
by: Hird, Max, et al.
Published: (2026)
Quantifying the effectiveness of linear preconditioning in Markov chain Monte Carlo
by: Hird, Max, et al.
Published: (2023)
by: Hird, Max, et al.
Published: (2023)
Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2024)
by: Wang, Congye, et al.
Published: (2024)
Adaptive Independent Sticky MCMC algorithms
by: Martino, L., et al.
Published: (2013)
by: Martino, L., et al.
Published: (2013)
Harnessing the Power of Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2025)
by: Wang, Congye, et al.
Published: (2025)
On the Computational Complexity of Private High-dimensional Model Selection
by: Roy, Saptarshi, et al.
Published: (2023)
by: Roy, Saptarshi, et al.
Published: (2023)
On Cyclical MCMC Sampling
by: Wang, Liwei, et al.
Published: (2024)
by: Wang, Liwei, et al.
Published: (2024)
Stochastic Approximation with Biased MCMC for Expectation Maximization
by: Gruffaz, Samuel, et al.
Published: (2024)
by: Gruffaz, Samuel, et al.
Published: (2024)
Reducing normalizing flow complexity for MCMC preconditioning
by: Nabergoj, David, et al.
Published: (2025)
by: Nabergoj, David, et al.
Published: (2025)
MCMC-driven learning
by: Bouchard-Côté, Alexandre, et al.
Published: (2024)
by: Bouchard-Côté, Alexandre, 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)
by: Corenflos, Adrien, et al.
Published: (2024)
Scalable Bayesian Inference for Generalized Linear Mixed Models via Stochastic Gradient MCMC
by: Berchuck, Samuel I., et al.
Published: (2024)
by: Berchuck, Samuel I., et al.
Published: (2024)
AutoStep: Locally adaptive involutive MCMC
by: Liu, Tiange, et al.
Published: (2024)
by: Liu, Tiange, et al.
Published: (2024)
Diffusion Generative Modelling for Divide-and-Conquer MCMC
by: Trojan, C., et al.
Published: (2024)
by: Trojan, C., et al.
Published: (2024)
Policy Gradients for Optimal Parallel Tempering MCMC
by: Zhao, Daniel, et al.
Published: (2024)
by: Zhao, Daniel, et al.
Published: (2024)
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
by: Du, Yilun, et al.
Published: (2023)
by: Du, Yilun, et al.
Published: (2023)
Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems
by: Cao, Lianghao, et al.
Published: (2024)
by: Cao, Lianghao, et al.
Published: (2024)
Comparison of parallel SMC and MCMC for Bayesian deep learning
by: Liang, Xinzhu, et al.
Published: (2024)
by: Liang, Xinzhu, et al.
Published: (2024)
PolytopeWalk: Sparse MCMC Sampling over Polytopes
by: Sun, Benny, et al.
Published: (2024)
by: Sun, Benny, et al.
Published: (2024)
Efficiently Vectorized MCMC on Modern Accelerators
by: Dance, Hugh, et al.
Published: (2025)
by: Dance, Hugh, et al.
Published: (2025)
Asymptotically exact variational flows via involutive MCMC kernels
by: Xu, Zuheng, et al.
Published: (2025)
by: Xu, Zuheng, et al.
Published: (2025)
JaxSGMC: Modular stochastic gradient MCMC in JAX
by: Thaler, Stephan, et al.
Published: (2025)
by: Thaler, Stephan, et al.
Published: (2025)
Distributed MCMC inference for Bayesian Non-Parametric Latent Block Model
by: Khoufache, Reda, et al.
Published: (2024)
by: Khoufache, Reda, et al.
Published: (2024)
Efficient MCMC Sampling with Expensive-to-Compute and Irregular Likelihoods
by: Rosato, Conor, et al.
Published: (2025)
by: Rosato, Conor, et al.
Published: (2025)
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
by: Yi, Zeji, et al.
Published: (2024)
by: Yi, Zeji, et al.
Published: (2024)
Non-Vacuous Certification of Transport MCMC via Oscillation-Controlled Normalizing Flows
by: Hu, Jun
Published: (2026)
by: Hu, Jun
Published: (2026)
Efficient Sampling on Riemannian Manifolds via Langevin MCMC
by: Cheng, Xiang, et al.
Published: (2024)
by: Cheng, Xiang, et al.
Published: (2024)
Learning to Explore for Stochastic Gradient MCMC
by: Kim, SeungHyun, et al.
Published: (2024)
by: Kim, SeungHyun, et al.
Published: (2024)
Bayesian neural networks via MCMC: a Python-based tutorial
by: Chandra, Rohitash, et al.
Published: (2023)
by: Chandra, Rohitash, et al.
Published: (2023)
Learning Multimodal Latent Space with EBM Prior and MCMC Inference
by: Yuan, Shiyu, et al.
Published: (2024)
by: Yuan, Shiyu, et al.
Published: (2024)
Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
by: Gonzalez, Emmanuel Anaya, et al.
Published: (2025)
by: Gonzalez, Emmanuel Anaya, et al.
Published: (2025)
Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)
by: Chen, Yujie, et al.
Published: (2025)
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems
by: Corenflos, Adrien, et al.
Published: (2023)
by: Corenflos, Adrien, et al.
Published: (2023)
Partially factorized variational inference for high-dimensional mixed models
by: Goplerud, Max, et al.
Published: (2023)
by: Goplerud, Max, et al.
Published: (2023)
Time Shifts to Reduce the Size of Reservoir Computers
by: Carroll, Thomas L., et al.
Published: (2022)
by: Carroll, Thomas L., et al.
Published: (2022)
The occlusion process: improving sampler performance with parallel computation and variational approximation
by: Hird, Max, et al.
Published: (2024)
by: Hird, Max, et al.
Published: (2024)
AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization
by: Bieringer, Sebastian, et al.
Published: (2023)
by: Bieringer, Sebastian, et al.
Published: (2023)
BERT-LSH: Reducing Absolute Compute For Attention
by: Li, Zezheng, et al.
Published: (2024)
by: Li, Zezheng, et al.
Published: (2024)
From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling
by: Renaud, Marien, et al.
Published: (2025)
by: Renaud, Marien, et al.
Published: (2025)
Scalable Distributed Algorithms for Size-Constrained Submodular Maximization in the MapReduce and Adaptive Complexity Models
by: Chen, Yixin, et al.
Published: (2022)
by: Chen, Yixin, et al.
Published: (2022)
Similar Items
-
A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
by: Hird, Max, et al.
Published: (2026) -
Quantifying the effectiveness of linear preconditioning in Markov chain Monte Carlo
by: Hird, Max, et al.
Published: (2023) -
Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2024) -
Adaptive Independent Sticky MCMC algorithms
by: Martino, L., et al.
Published: (2013) -
Harnessing the Power of Reinforcement Learning for Adaptive MCMC
by: Wang, Congye, et al.
Published: (2025)