Cover Image

IID Sampling from Intractable Distributions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Bhattacharya, Sourabh
Format:	Preprint
Published:	2021
Subjects:	Computation Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bayesian Levy-Dynamic Spatio-Temporal Process: Towards Big Data Analysis
by: Bhattacharya, Sourabh
Published: (2021)

Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems
by: Kang, Bokgyeong, et al.
Published: (2021)

Exact MCMC for Intractable Proposals
by: Kakkad, Dwija, et al.
Published: (2024)

Bayesian Nonparametrics for Gene-Gene and Gene-Environment Interactions in Case-Control Studies: A Synthesis and Extension
by: Bhattacharya, Durba, et al.
Published: (2026)

How Ominous is the Premonition of Future Global Warming?
by: Chatterjee, Debashis, et al.
Published: (2020)

Simulation-Based Fitting of Intractable Models via Sequential Sampling and Local Smoothing
by: Masarotto, Guido
Published: (2025)

The Bayesian Reflex: Online Learning as the Autonomic Nervous System of Modern and Future AI
by: Bhattacharya, Durba, et al.
Published: (2026)

A New Spatio-Temporal Model Exploiting Hamiltonian Equations
by: Mazumder, Satyaki, et al.
Published: (2022)

A Delayed Acceptance Auxiliary Variable MCMC for Spatial Models with Intractable Likelihood Function
by: Lee, Jong Hyeon, et al.
Published: (2025)

Algorithms for Models with Intractable Normalizing Functions
by: Haran, Murali, et al.
Published: (2026)

Sampling from Conditional Distributions of Simplified Vines
by: Hanebeck, Ariane, et al.
Published: (2025)

Estimating Intractable Posterior Distributions through Gaussian Process regression and Metropolis-adjusted Langevin procedure
by: Perrin, Guillaume, et al.
Published: (2025)

Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants
by: Chen, Yujie, et al.
Published: (2024)

Conjugate Generalised Bayesian Inference for Discrete Doubly Intractable Problems
by: Laplante, William, et al.
Published: (2025)

Graph-Enabled Fast MCMC Sampling with an Unknown High-Dimensional Prior Distribution
by: Zhong, Chenyang, et al.
Published: (2024)

Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods
by: Walchessen, Julia, et al.
Published: (2023)

Robust Simulation Based Inference Through Robust Optimal Transport
by: Jacobs, Peter Matthew, et al.
Published: (2026)

RCT Rejection Sampling for Causal Estimation Evaluation
by: Keith, Katherine A., et al.
Published: (2023)

Insufficient Gibbs Sampling
by: Luciano, Antoine, et al.
Published: (2023)

Bridge Sampling Diagnostics
by: Micaletto, Giorgio, et al.
Published: (2025)

Sampling the Bayesian Elastic Net
by: Hans, Christopher M., et al.
Published: (2024)

Direct Sampling with a Step Function
by: Raim, Andrew M.
Published: (2022)

Rejection Sampling with Vertical Weighted Strips
by: Raim, Andrew M., et al.
Published: (2024)

Computation of Optimal Type-II Progressing Censoring Scheme Using Genetic Algorithm Approach
by: Roy, Ujjwal, et al.
Published: (2025)

An Efficient Sampling from Circular Distributions and its Extension to Toroidal Distributions
by: Biswas, Surojit, et al.
Published: (2024)

Finite Population Sampling as n to N: Empirical Evidence for the Transition from Inference to Accuracy
by: Crowhurst, Mike
Published: (2026)

Optimal Sampling for Kernel Quadrature on Unbounded Domains
by: Bandoni, Edoardo, et al.
Published: (2026)

Recursive Adaptive Importance Sampling with Optimal Replenishment
by: Barreto, Daniel Würzler, et al.
Published: (2025)

MCMC Importance Sampling via Moreau-Yosida Envelopes
by: Shukla, Apratim, et al.
Published: (2025)

Sub-Cauchy Sampling: Escaping the Dark Side of the Moon
by: Grazzi, Sebastiano, et al.
Published: (2026)

A Framework to Analyze Multiscale Sampling MCMC Methods
by: Seiffert, Lucas, et al.
Published: (2025)

Finite Sample Valid Inference via Calibrated Bootstrap
by: Jiang, Yiran, et al.
Published: (2024)

An Optimal Transport-Based Generative Model for Bayesian Posterior Sampling
by: Li, Ke, et al.
Published: (2025)

Estimating the Effective Sample Size for an inverse problem in subsurface flows
by: Seiffert, Lucas, et al.
Published: (2024)

MCBench: A Benchmark Suite for Monte Carlo Sampling Algorithms
by: Ding, Zeyu, et al.
Published: (2025)

Enhancing Sample Quality through Minimum Energy Importance Weights
by: Huang, Chaofan, et al.
Published: (2023)

Parameter Estimation of State Space Models Using Particle Importance Sampling
by: Gao, Yuxiong, et al.
Published: (2025)

Bioequivalence Design with Sampling Distribution Segments
by: Hagar, Luke, et al.
Published: (2023)

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

Penalized Likelihood Approach for the Four-parameter Kappa Distribution
by: Papukdee, Nipada, et al.
Published: (2024)