变分推断论文趋势 2023–2026

主要结论

• 变分推断论文从 2023 年的 106 篇降到 2026 年的 91 篇，热度在回落。
• NeurIPS 是发变分推断论文最多的会议，2023–2026 年共 124 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是采样方法：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 6 篇。
• 在「概率与贝叶斯」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的高斯过程是 2.2 倍，变分推断是 0.9 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部变分推断论文

共 124 篇，第 1 / 3 页

1. NeurIPS 2026A Reproducible Evaluation Protocol for Quantum Non-Linearity in Variational Quantum Models
2. NeurIPS 2026Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities
3. NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
4. NeurIPS 2026Beyond Maximum Likelihood: Variational Inequality Estimation for Generalized Linear Models
5. NeurIPS 2026Denoising Implicit Variational Inference
6. NeurIPS 2026Differentiable Systematic Resampling for Variational Sequential Monte Carlo
7. NeurIPS 2026Dual-Space Preconditioning for Variational Inequalities and Root-Finding Problems
8. NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
9. NeurIPS 2026Even More Guarantees for Variational Inference in the Presence of Symmetries
10. NeurIPS 2026Faster Rates For Federated Variational Inequalities
11. NeurIPS 2026Filtered-Trace Online Variational Training for Probabilistic Spiking Neural Networks
12. NeurIPS 2026Flow-Transformed Implicit Processes for Function-Space Variational Inference
13. NeurIPS 2026Hierarchical Variational Policies for Reward-Guided Diffusion
14. NeurIPS 2026Implicit Neural Representations for Variational Problems on Graphons
15. NeurIPS 2026Learning from Language Feedback via Variational Policy Distillation
16. NeurIPS 2026LEVDA: Latent Ensemble Variational Data Assimilation via Differentiable Dynamics
17. NeurIPS 2026Parameter Exploration for RLVR via Variational Learning
18. NeurIPS 2026Random-Projection Tree Stein Variational Gradient Descent
19. NeurIPS 2026Score-based Variational Inference via Quantum Maximally Mixed States
20. NeurIPS 2026Support-Safe Variational Hybrid Filtering for Contact-Mode and Sparse-Law Recovery
21. NeurIPS 2026Symmetry Guarantees Statistic Recovery in Variational Inference
22. NeurIPS 2026TailAdapt: Heavy-Tailed Sparse Variational Adaptation for Long-Tailed Class Incremental Learning
23. NeurIPS 2026Uncovering Semantic Hierarchies in Text-Attributed Graphs via Variational EM-based LLM–GNN Synergy
24. NeurIPS 2026Variational Active Flow Matching for Discrete Online Black-Box Optimization
25. NeurIPS 2026Variational Consequence-Driven Offline Reinforcement Learning
26. NeurIPS 2026Variational Cover Modification Steganography
27. NeurIPS 2026Variational Inference via Entropic Transport Descent
28. NeurIPS 2026Variational Trajectory Optimization of Anisotropic Diffusion Schedules
29. NeurIPS 2026VESPO: Variational Sequence-level Soft Policy Optimization for Off-Policy LLM Training
30. NeurIPS 2026xVGAE: A Hierarchical Variational Graph Autoencoder for Exchangeable Graphs
31. NeurIPS 2025Amortized Variational Transdimensional Inference
32. NeurIPS 2025Amplifying Prominent Representations in Multimodal Learning via Variational Dirichlet Process
33. NeurIPS 2025Asymptotically exact variational flows via involutive MCMC kernels
34. NeurIPS 2025Brain-like Variational Inference
35. NeurIPS 2025Covariate-moderated Empirical Bayes Matrix Factorization
36. NeurIPS 2025DualFocus: Depth from Focus with Spatio-Focal Dual Variational Constraints
37. NeurIPS 2025ESCORT: Efficient Stein-variational and Sliced Consistency-Optimized Temporal Belief Representation for POMDPs
38. NeurIPS 2025Fisher meets Feynman: score-based variational inference with a product of experts
39. NeurIPS 2025HoT-VI: Reparameterizable Variational Inference for Capturing Instance-Level High-Order Correlations
40. NeurIPS 2025Identifying interactions across brain areas while accounting for individual-neuron dynamics with a Transformer-based variational autoencoder
41. NeurIPS 2025Large Language Bayes
42. NeurIPS 2025Learning Stochastic Multiscale Models
43. NeurIPS 2025Least squares variational inference
44. NeurIPS 2025LoRA-EnVar: Parameter-Efficient Hybrid Ensemble Variational Assimilation for Weather Forecasting
45. NeurIPS 2025Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference
46. NeurIPS 2025NeuralSurv: Deep Survival Analysis with Bayesian Uncertainty Quantification
47. NeurIPS 2025ProDAG: Projected Variational Inference for Directed Acyclic Graphs
48. NeurIPS 2025Quantifying Uncertainty in the Presence of Distribution Shifts
49. NeurIPS 2025Solving Inverse Problems with FLAIR
50. NeurIPS 2025Variational Inference with Mixtures of Isotropic Gaussians

常见问题

2023–2026 年四大会议一共有多少篇变分推断论文？

共 359 篇，按年份分别是 2023 年 106 篇、2024 年 76 篇、2025 年 86 篇、2026 年 91 篇。

NeurIPS 2026 有多少篇变分推断论文？

NeurIPS 2026 有 30 篇变分推断论文，上一届是 28 篇。

ICLR 2026 有多少篇变分推断论文？

ICLR 2026 有 23 篇变分推断论文，上一届是 28 篇。

ICML 2026 有多少篇变分推断论文？

ICML 2026 有 35 篇变分推断论文，上一届是 28 篇。

CVPR 2026 有多少篇变分推断论文？

CVPR 2026 有 3 篇变分推断论文，上一届是 2 篇。

哪个会议的变分推断论文最多？

NeurIPS，2023–2026 年共 124 篇。