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 76 篇，第 1 / 2 页

1. CVPR 2024Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
2. CVPR 2024SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
3. CVPR 2024WorDepth: Variational Language Prior for Monocular Depth Estimation
4. ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
5. ICLR 2024A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
6. ICLR 2024A Variational Perspective on Solving Inverse Problems with Diffusion Models
7. ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
8. ICLR 2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
9. ICLR 2024Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
10. ICLR 2024Conditional Variational Diffusion Models
11. ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
12. ICLR 2024DiffEnc: Variational Diffusion with a Learned Encoder
13. ICLR 2024Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
14. ICLR 2024Fast Ensembling with Diffusion Schrödinger Bridge
15. ICLR 2024Fiber Monte Carlo
16. ICLR 2024Forward $\chi^2$ Divergence Based Variational Importance Sampling
17. ICLR 2024Input-gradient space particle inference for neural network ensembles
18. ICLR 2024Kernelised Normalising Flows
19. ICLR 2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments
20. ICLR 2024MINDE: Mutual Information Neural Diffusion Estimation
21. ICLR 2024R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
22. ICLR 2024Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms
23. ICLR 2024Stochastic Gradient Descent for Gaussian Processes Done Right
24. ICLR 2024Training Bayesian Neural Networks with Sparse Subspace Variational Inference
25. ICLR 2024Transport meets Variational Inference: Controlled Monte Carlo Diffusions
26. ICLR 2024Uncertainty Quantification via Stable Distribution Propagation
27. ICLR 2024Variational Bayesian Last Layers
28. ICLR 2024Variational Inference for SDEs Driven by Fractional Noise
29. ICML 2024$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
30. ICML 2024Adaptive Observation Cost Control for Variational Quantum Eigensolvers
31. ICML 2024Amortized Variational Deep Kernel Learning
32. ICML 2024Batch and match: black-box variational inference with a score-based divergence
33. ICML 2024Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
34. ICML 2024Efficient Mixture Learning in Black-Box Variational Inference
35. ICML 2024Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
36. ICML 2024High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
37. ICML 2024Kernel Semi-Implicit Variational Inference
38. ICML 2024Language-guided Skill Learning with Temporal Variational Inference
39. ICML 2024Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
40. ICML 2024Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
41. ICML 2024Logistic Variational Bayes Revisited
42. ICML 2024Online Variational Sequential Monte Carlo
43. ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
44. ICML 2024Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
45. ICML 2024Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
46. ICML 2024Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
47. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
48. ICML 2024Understanding Stochastic Natural Gradient Variational Inference
49. ICML 2024Variational Inference with Coverage Guarantees in Simulation-Based Inference
50. ICML 2024Variational Learning is Effective for Large Deep Networks

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。