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 2 of 8

51. ICML 2026Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
52. ICML 2026Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
53. ICML 2026Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture – Bridging Predictive and Generative Self-Supervised Learning
54. ICML 2026Variational Adapter for Cross-modal Similarity Representation
55. ICML 2026Variational Entropic Optimal Transport
56. ICML 2026Variational Inference for Uncertain Optimal Transport via Sinkhorn Parametrization
57. ICML 2026Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
58. ICML 2026Variational Learning of Disentangled Representations
59. ICML 2026Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
60. ICML 2026Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance
61. ICML 2026VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
62. NeurIPS 2026A Reproducible Evaluation Protocol for Quantum Non-Linearity in Variational Quantum Models
63. NeurIPS 2026Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities
64. NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
65. NeurIPS 2026Beyond Maximum Likelihood: Variational Inequality Estimation for Generalized Linear Models
66. NeurIPS 2026Denoising Implicit Variational Inference
67. NeurIPS 2026Differentiable Systematic Resampling for Variational Sequential Monte Carlo
68. NeurIPS 2026Dual-Space Preconditioning for Variational Inequalities and Root-Finding Problems
69. NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
70. NeurIPS 2026Even More Guarantees for Variational Inference in the Presence of Symmetries
71. NeurIPS 2026Faster Rates For Federated Variational Inequalities
72. NeurIPS 2026Filtered-Trace Online Variational Training for Probabilistic Spiking Neural Networks
73. NeurIPS 2026Flow-Transformed Implicit Processes for Function-Space Variational Inference
74. NeurIPS 2026Hierarchical Variational Policies for Reward-Guided Diffusion
75. NeurIPS 2026Implicit Neural Representations for Variational Problems on Graphons
76. NeurIPS 2026Learning from Language Feedback via Variational Policy Distillation
77. NeurIPS 2026LEVDA: Latent Ensemble Variational Data Assimilation via Differentiable Dynamics
78. NeurIPS 2026Parameter Exploration for RLVR via Variational Learning
79. NeurIPS 2026Random-Projection Tree Stein Variational Gradient Descent
80. NeurIPS 2026Score-based Variational Inference via Quantum Maximally Mixed States
81. NeurIPS 2026Support-Safe Variational Hybrid Filtering for Contact-Mode and Sparse-Law Recovery
82. NeurIPS 2026Symmetry Guarantees Statistic Recovery in Variational Inference
83. NeurIPS 2026TailAdapt: Heavy-Tailed Sparse Variational Adaptation for Long-Tailed Class Incremental Learning
84. NeurIPS 2026Uncovering Semantic Hierarchies in Text-Attributed Graphs via Variational EM-based LLM–GNN Synergy
85. NeurIPS 2026Variational Active Flow Matching for Discrete Online Black-Box Optimization
86. NeurIPS 2026Variational Consequence-Driven Offline Reinforcement Learning
87. NeurIPS 2026Variational Cover Modification Steganography
88. NeurIPS 2026Variational Inference via Entropic Transport Descent
89. NeurIPS 2026Variational Trajectory Optimization of Anisotropic Diffusion Schedules
90. NeurIPS 2026VESPO: Variational Sequence-level Soft Policy Optimization for Off-Policy LLM Training
91. NeurIPS 2026xVGAE: A Hierarchical Variational Graph Autoencoder for Exchangeable Graphs
92. CVPR 2025Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
93. CVPR 2025Robust Multimodal Survival Prediction with Conditional Latent Differentiation Variational AutoEncoder
94. ICLR 2025Accelerating Neural ODEs: A Variational Formulation-based Approach
95. ICLR 2025Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
96. ICLR 2025Connecting Federated ADMM to Bayes
97. ICLR 2025Efficient Interpolation between Extragradient and Proximal Methods for Weak MVIs
98. ICLR 2025ELBOing Stein: Variational Bayes with Stein Mixture Inference
99. ICLR 2025Flow-based Variational Mutual Information: Fast and Flexible Approximations
100. ICLR 2025Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent

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.