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

124 papers, page 2 of 3

51. NeurIPS 2025Variational Learning Finds Flatter Solutions at the Edge of Stability
52. NeurIPS 2025Variational Polya Tree
53. NeurIPS 2025Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action
54. NeurIPS 2025Variational Supervised Contrastive Learning
55. NeurIPS 2025Variational Task Vector Composition
56. NeurIPS 2025Variational Uncertainty Decomposition for In-Context Learning
57. NeurIPS 2025VERA: Variational Inference Framework for Jailbreaking Large Language Models
58. NeurIPS 2025VIKING: Deep variational inference with stochastic projections
59. NeurIPS 2024Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families
60. NeurIPS 2024Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
61. NeurIPS 2024EigenVI: score-based variational inference with orthogonal function expansions
62. NeurIPS 2024Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
63. NeurIPS 2024Fearless Stochasticity in Expectation Propagation
64. NeurIPS 2024Globally Convergent Variational Inference
65. NeurIPS 2024Inference of Neural Dynamics Using Switching Recurrent Neural Networks
66. NeurIPS 2024Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities
67. NeurIPS 2024LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
68. NeurIPS 2024Noether's Razor: Learning Conserved Quantities
69. NeurIPS 2024On Divergence Measures for Training GFlowNets
70. NeurIPS 2024Particle Semi-Implicit Variational Inference
71. NeurIPS 2024Poisson Variational Autoencoder
72. NeurIPS 2024Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
73. NeurIPS 2024Quadratic Quantum Variational Monte Carlo
74. NeurIPS 2024Rejection via Learning Density Ratios
75. NeurIPS 2024Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
76. NeurIPS 2024TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing
77. NeurIPS 2024Unscrambling disease progression at scale: fast inference of event permutations with optimal transport
78. NeurIPS 2024Variational Delayed Policy Optimization
79. NeurIPS 2024Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting
80. NeurIPS 2024VISA: Variational Inference with Sequential Sample-Average Approximations
81. NeurIPS 2023[Re] Variational Neural Cellular Automata
82. NeurIPS 2023A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
83. NeurIPS 2023A Heavy-Tailed Algebra for Probabilistic Programming
84. NeurIPS 2023A Variational Perspective on High-Resolution ODEs
85. NeurIPS 2023AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders
86. NeurIPS 2023Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
87. NeurIPS 2023Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
88. NeurIPS 2023Approximate inference of marginals using the IBIA framework
89. NeurIPS 2023ARTree: A Deep Autoregressive Model for Phylogenetic Inference
90. NeurIPS 2023Attention as Implicit Structural Inference
91. NeurIPS 2023Conditional Matrix Flows for Gaussian Graphical Models
92. NeurIPS 2023Conformalized matrix completion
93. NeurIPS 2023Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier
94. NeurIPS 2023Embracing the chaos: analysis and diagnosis of numerical instability in variational flows
95. NeurIPS 2023End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics
96. NeurIPS 2023Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
97. NeurIPS 2023Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
98. NeurIPS 2023Gacs-Korner Common Information Variational Autoencoder
99. NeurIPS 2023GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
100. NeurIPS 2023Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration

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.