Variational Inference papers, 2023–2026

Key findings

• Variational Inference fell from 106 papers in 2023 to 91 in 2026, so interest is cooling.
• NeurIPS publishes the most Variational Inference work: 124 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Sampling Methods: papers tagged with both rose from 1 in 2023 to 6 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #5 by 2026 paper count; the fastest grower in the group, Gaussian Processes, is up 2.2x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Reproducible Evaluation Protocol for Quantum Non-Linearity in Variational Quantum Models
• ICML 2026Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
• ICLR 2026Optimizing Data Augmentation through Bayesian Model Selection
• CVPR 2026BrepVGAE Variational Graph Autoencoder with Unified Latent Representation for B-rep
• NeurIPS 2025Covariate-moderated Empirical Bayes Matrix Factorization
• ICML 2025A Variational Information Theoretic Approach to Out-of-Distribution Detection
• ICLR 2025Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
• CVPR 2025Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
• NeurIPS 2024Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
• ICML 2024Amortized Variational Deep Kernel Learning
• ICLR 2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
• CVPR 2024WorDepth: Variational Language Prior for Monocular Depth Estimation
• NeurIPS 2023[Re] Variational Neural Cellular Automata
• ICML 2023Coupled Variational Autoencoder
• ICLR 2023A VAE for Transformers with Nonparametric Variational Information Bottleneck
• CVPR 2023Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization
• NeurIPS 2026Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities
• ICML 2026Dual-stage Contrastive Learning-enhanced Multi-view Variational Clustering
• ICLR 2026Pareto Variational Autoencoder
• CVPR 2026Variational Graph-based Normal Integration

All Variational Inference papers

26 papers, page 1 of 1

1. ICML 2024$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
2. ICML 2024Adaptive Observation Cost Control for Variational Quantum Eigensolvers
3. ICML 2024Amortized Variational Deep Kernel Learning
4. ICML 2024Batch and match: black-box variational inference with a score-based divergence
5. ICML 2024Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
6. ICML 2024Efficient Mixture Learning in Black-Box Variational Inference
7. ICML 2024Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
8. ICML 2024High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
9. ICML 2024Kernel Semi-Implicit Variational Inference
10. ICML 2024Language-guided Skill Learning with Temporal Variational Inference
11. ICML 2024Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
12. ICML 2024Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
13. ICML 2024Logistic Variational Bayes Revisited
14. ICML 2024Online Variational Sequential Monte Carlo
15. ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
16. ICML 2024Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
17. ICML 2024Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
18. ICML 2024Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
19. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
20. ICML 2024Understanding Stochastic Natural Gradient Variational Inference
21. ICML 2024Variational Inference with Coverage Guarantees in Simulation-Based Inference
22. ICML 2024Variational Learning is Effective for Large Deep Networks
23. ICML 2024Variational Linearized Laplace Approximation for Bayesian Deep Learning
24. ICML 2024Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
25. ICML 2024Variational Schrödinger Diffusion Models
26. ICML 2024Why do Variational Autoencoders Really Promote Disentanglement?

FAQ

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

359 in total: 106 in 2023, 76 in 2024, 86 in 2025, 91 in 2026.

How many Variational Inference papers are at NeurIPS 2026?

NeurIPS 2026 has 30 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at ICLR 2026?

ICLR 2026 has 23 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at ICML 2026?

ICML 2026 has 35 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at CVPR 2026?

CVPR 2026 has 3 Variational Inference papers, versus 2 the year before.

Which conference publishes the most Variational Inference papers?

NeurIPS, with 124 papers from 2023 to 2026.