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

111 papers, page 2 of 3

51. ICML 2025Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference
52. ICML 2025Neural Guided Diffusion Bridges
53. ICML 2025New Bounds for Sparse Variational Gaussian Processes
54. ICML 2025Pareto-frontier Entropy Search with Variational Lower Bound Maximization
55. ICML 2025Revisiting Unbiased Implicit Variational Inference
56. ICML 2025Score Matching with Missing Data
57. ICML 2025Synonymous Variational Inference for Perceptual Image Compression
58. ICML 2025Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
59. ICML 2025Variational Counterfactual Intervention Planning to Achieve Target Outcomes
60. ICML 2025Variational Learning of Fractional Posteriors
61. ICML 2025Variational Phylogenetic Inference with Products over Bipartitions
62. ICML 2025Variational Rectified Flow Matching
63. ICML 2025VCT: Training Consistency Models with Variational Noise Coupling
64. ICML 2024$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
65. ICML 2024Adaptive Observation Cost Control for Variational Quantum Eigensolvers
66. ICML 2024Amortized Variational Deep Kernel Learning
67. ICML 2024Batch and match: black-box variational inference with a score-based divergence
68. ICML 2024Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
69. ICML 2024Efficient Mixture Learning in Black-Box Variational Inference
70. ICML 2024Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
71. ICML 2024High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
72. ICML 2024Kernel Semi-Implicit Variational Inference
73. ICML 2024Language-guided Skill Learning with Temporal Variational Inference
74. ICML 2024Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
75. ICML 2024Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
76. ICML 2024Logistic Variational Bayes Revisited
77. ICML 2024Online Variational Sequential Monte Carlo
78. ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
79. ICML 2024Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
80. ICML 2024Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
81. ICML 2024Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
82. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
83. ICML 2024Understanding Stochastic Natural Gradient Variational Inference
84. ICML 2024Variational Inference with Coverage Guarantees in Simulation-Based Inference
85. ICML 2024Variational Learning is Effective for Large Deep Networks
86. ICML 2024Variational Linearized Laplace Approximation for Bayesian Deep Learning
87. ICML 2024Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
88. ICML 2024Variational Schrödinger Diffusion Models
89. ICML 2024Why do Variational Autoencoders Really Promote Disentanglement?
90. ICML 2023A Fast Optimistic Method for Monotone Variational Inequalities
91. ICML 2023Coupled Variational Autoencoder
92. ICML 2023Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference
93. ICML 2023Effective and Efficient Structural Inference with Reservoir Computing
94. ICML 2023Fast Inference from Transformers via Speculative Decoding
95. ICML 2023Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space
96. ICML 2023Free-Form Variational Inference for Gaussian Process State-Space Models
97. ICML 2023Markovian Gaussian Process Variational Autoencoders
98. ICML 2023Metagenomic Binning using Connectivity-constrained Variational Autoencoders
99. ICML 2023MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
100. ICML 2023MixFlows: principled variational inference via mixed 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.