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 2 / 3 页

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

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。