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

359 papers, page 1 of 8

1. CVPR 2026BrepVGAE Variational Graph Autoencoder with Unified Latent Representation for B-rep
2. CVPR 2026Variational Graph-based Normal Integration
3. CVPR 2026VENI Variational Encoder for Natural Illumination
4. ICLR 2026Amortising Inference and Meta-Learning Priors in Neural Networks
5. ICLR 2026Bayesian Parameter Shift Rules in Variational Quantum Eigensolvers
6. ICLR 2026Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers
7. ICLR 2026Decision Aggregation under Quantal Response
8. ICLR 2026Diffusion Bridge Variational Inference for Deep Gaussian Processes
9. ICLR 2026Discrete Variational Autoencoding via Policy Search
10. ICLR 2026Flow Map Learning via Games
11. ICLR 2026Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster
12. ICLR 2026Learning Boltzmann Generators via Constrained Mass Transport
13. ICLR 2026Learning Survival Distributions with Individually Calibrated Asymmetric Laplace Distribution
14. ICLR 2026Multilevel Control Functional
15. ICLR 2026Neural Posterior Estimation with Latent Basis Expansions
16. ICLR 2026On the Mechanisms of Collaborative Learning in VAE Recommenders
17. ICLR 2026Optimizing Data Augmentation through Bayesian Model Selection
18. ICLR 2026Pareto Variational Autoencoder
19. ICLR 2026Permutation-Consistent Variational Encoding for Incomplete Multi-View Multi-Label Classification
20. ICLR 2026Proximal Diffusion Neural Sampler
21. ICLR 2026Random-projection ensemble dimension reduction
22. ICLR 2026Robust Generalized Schr\"{o}dinger Bridge via Sparse Variational Gaussian Processes
23. ICLR 2026Score-Based Density Estimation from Pairwise Comparisons
24. ICLR 2026Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders
25. ICLR 2026Variational Deep Learning via Implicit Regularization
26. ICLR 2026Variational Inference for Cyclic Learning
27. ICML 2026A hitchhiker's guide to Poisson gradient estimation
28. ICML 2026A Unifying View of Variational Generative Wasserstein Flows
29. ICML 2026Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
30. ICML 2026Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
31. ICML 2026Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
32. ICML 2026Copula-SVI: Vine-Copula Variational Inference with Stein Refining for Instance-Level Correlation Capturing
33. ICML 2026Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference
34. ICML 2026Distribution Matching Variational AutoEncoder
35. ICML 2026Do-Prompt: Causal Interventions Meet Variational Prompt Bottlenecks
36. ICML 2026Dual-stage Contrastive Learning-enhanced Multi-view Variational Clustering
37. ICML 2026Efficient Online Variational Estimation via Monte Carlo Sampling
38. ICML 2026Gaussian Mean Field Variational Inference can Overestimate Predictive Variance
39. ICML 2026Hölder++: Improving Quality-Coherence Trade-off in Multimodal VAEs
40. ICML 2026HVAE: Hyperbolic Variational Autoencoder For Flexible Knowledge Transfer Across Multiple Domains
41. ICML 2026Last-Iterate Convergence of Regularized Gradient Methods for Stochastic Monotone Variational Inequalities
42. ICML 2026MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
43. ICML 2026Monotonic Variational Gaussian Process for Efficient Data Collection
44. ICML 2026Native Spatio-Temporal 4D Variational Autoencoder
45. ICML 2026Particles Don’t Care About Z: Towards Scaling Entropy Estimation of Unnormalized Densities
46. ICML 2026Phase-Type Variational Autoencoders for Heavy-Tailed Data
47. ICML 2026Predictive variational inference: Learn the predictively optimal posterior distribution
48. ICML 2026Rényi Diffusion Models
49. ICML 2026Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
50. ICML 2026Spectral Bridge Variational Inference: Dynamic LoRA via Bures-Wasserstein Gradient Flows

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.