Sampling Methods papers, 2023–2026

Key findings

• Sampling Methods went from 122 papers in 2023 to 195 in 2026, roughly 1.6x in three years.
• NeurIPS publishes the most Sampling Methods work: 221 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Monte Carlo Tree Search: papers tagged with both rose from 4 in 2023 to 31 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #2 by 2026 paper count; the fastest grower in the group, Gaussian Processes, is up 2.2x versus 1.6x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Model of Diverse Sampling from Language Models
• ICML 2026BFTS: Thompson Sampling with Bayesian Additive Regression Trees
• ICLR 2026Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling
• CVPR 2026Active Inference for Micro-Gesture Recognition EFE-Guided Temporal Sampling and Adaptive
• NeurIPS 2025Antidistillation Sampling
• ICML 2025Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
• ICLR 2025Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
• CVPR 2025AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual Learning
• NeurIPS 2024In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies
• ICML 2024Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
• ICLR 2024Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
• CVPR 2024G-FARS: Gradient-Field-based Auto-Regressive Sampling for 3D Part Grouping
• NeurIPS 2023A Dynamical System View of Langevin-Based Non-Convex Sampling
• ICML 2023Adaptive Annealed Importance Sampling with Constant Rate Progress
• ICLR 2023Any-scale Balanced Samplers for Discrete Space
• CVPR 2023Change-Aware Sampling and Contrastive Learning for Satellite Images
• NeurIPS 2026A Semantic-Sampling Framework for Evaluating Calibration in Open-Ended Question Answering
• ICML 2026Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
• ICLR 2026On Coreset for LASSO Regression Problem with Sensitivity Sampling
• CVPR 2026Designing Instance-Level Sampling Schedules via REINFORCE with James-Stein Shrinkage

All Sampling Methods papers

640 papers, page 9 of 13

401. ICLR 2024Fiber Monte Carlo
402. ICLR 2024Forward $\chi^2$ Divergence Based Variational Importance Sampling
403. ICLR 2024From Posterior Sampling to Meaningful Diversity in Image Restoration
404. ICLR 2024Improved Active Learning via Dependent Leverage Score Sampling
405. ICLR 2024Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
406. ICLR 2024Improved sampling via learned diffusions
407. ICLR 2024IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
408. ICLR 2024Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
409. ICLR 2024Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited
410. ICLR 2024Learning to Solve Bilevel Programs with Binary Tender
411. ICLR 2024On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
412. ICLR 2024One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
413. ICLR 2024Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
414. ICLR 2024Order-Preserving GFlowNets
415. ICLR 2024Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
416. ICLR 2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
417. ICLR 2024Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
418. ICLR 2024Probabilistically Rewired Message-Passing Neural Networks
419. ICLR 2024Protein Discovery with Discrete Walk-Jump Sampling
420. ICLR 2024Reverse Diffusion Monte Carlo
421. ICLR 2024Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
422. ICLR 2024Variational Bayesian Last Layers
423. ICML 2024$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
424. ICML 2024A sampling theory perspective on activations for implicit neural representations
425. ICML 2024A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models
426. ICML 2024Accelerated Speculative Sampling Based on Tree Monte Carlo
427. ICML 2024Accelerating Parallel Sampling of Diffusion Models
428. ICML 2024Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction
429. ICML 2024Ai-sampler: Adversarial Learning of Markov kernels with involutive maps
430. ICML 2024Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
431. ICML 2024Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
432. ICML 2024Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
433. ICML 2024Bifurcated Attention for Single-Context Large-Batch Sampling
434. ICML 2024Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
435. ICML 2024Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
436. ICML 2024Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
437. ICML 2024Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond
438. ICML 2024Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution
439. ICML 2024Diffusion Posterior Sampling is Computationally Intractable
440. ICML 2024Diffusion Rejection Sampling
441. ICML 2024Diffusive Gibbs Sampling
442. ICML 2024EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
443. ICML 2024Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
444. ICML 2024Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling
445. ICML 2024Embarrassingly Parallel GFlowNets
446. ICML 2024EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
447. ICML 2024Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
448. ICML 2024Estimating the Permanent by Nesting Importance Sampling
449. ICML 2024Fast Sampling-Based Sketches for Tensors
450. ICML 2024Faster Sampling via Stochastic Gradient Proximal Sampler

FAQ

How many Sampling Methods papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

640 in total: 122 in 2023, 156 in 2024, 167 in 2025, 195 in 2026.

How many Sampling Methods papers are at NeurIPS 2026?

NeurIPS 2026 has 64 Sampling Methods papers, versus 67 the year before.

How many Sampling Methods papers are at ICLR 2026?

ICLR 2026 has 46 Sampling Methods papers, versus 48 the year before.

How many Sampling Methods papers are at ICML 2026?

ICML 2026 has 71 Sampling Methods papers, versus 36 the year before.

How many Sampling Methods papers are at CVPR 2026?

CVPR 2026 has 14 Sampling Methods papers, versus 16 the year before.

Which conference publishes the most Sampling Methods papers?

NeurIPS, with 221 papers from 2023 to 2026.