贝叶斯深度学习论文趋势 2023–2026

主要结论

• 贝叶斯深度学习论文从 2023 年的 112 篇增长到 2026 年的 112 篇，三年间扩大到约 1.0 倍。
• NeurIPS 是发贝叶斯深度学习论文最多的会议，2023–2026 年共 165 篇，占四个会议总量的 40%。
• 交叉方向里涨得最快的是驾驶仿真：同时属于两个主题的论文从 2023 年的 5 篇增至 2026 年的 11 篇。
• 在「概率与贝叶斯」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的高斯过程是 2.2 倍，贝叶斯深度学习是 1.0 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 2026Approximate Bayesian inference with exchangeable distributions for neurosymbolic AI
• ICML 2026A Bayesian Approach to Quantify the Uncertainty of Human Ratings in a Single-Instance Multimodal Framework
• ICLR 2026Bayesian Neural Networks for Functional ANOVA Model
• CVPR 2026CGU-Bayes Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization
• NeurIPS 2025A Bayesian Approach to Contextual Dynamic Pricing using the Proportional Hazards Model with Discrete Price Data
• ICML 2025BARNN: A Bayesian Autoregressive and Recurrent Neural Network
• ICLR 2025Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior
• CVPR 2025HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
• NeurIPS 2024Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
• ICML 2024Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
• ICLR 2024A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
• CVPR 2024Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
• NeurIPS 2023A Bayesian Approach To Analysing Training Data Attribution In Deep Learning
• ICML 2023Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?
• ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
• CVPR 2023Bayesian Posterior Approximation With Stochastic Ensembles
• NeurIPS 2026BO-Arena: An Evolving Benchmark for High-Dimensional Bayesian Optimisation
• ICML 2026Bayesian Gated Non-Negative Contrastive Learning
• ICLR 2026Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
• CVPR 2026Evidential Deep Partial Label Learning to Quantify Disambiguation Uncertainty

全部贝叶斯深度学习论文

共 30 篇，第 1 / 1 页

1. NeurIPS 2024A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings
2. NeurIPS 2024A Metalearned Neural Circuit for Nonparametric Bayesian Inference
3. NeurIPS 2024Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
4. NeurIPS 2024Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
5. NeurIPS 2024Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
6. NeurIPS 2024Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
7. NeurIPS 2024Block Sparse Bayesian Learning: A Diversified Scheme
8. NeurIPS 2024BMRS: Bayesian Model Reduction for Structured Pruning
9. NeurIPS 2024Conjugate Bayesian Two-step Change Point Detection for Hawkes Process
10. NeurIPS 2024Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA
11. NeurIPS 2024Fixed Confidence Best Arm Identification in the Bayesian Setting
12. NeurIPS 2024FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
13. NeurIPS 2024Gradients of Functions of Large Matrices
14. NeurIPS 2024Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
15. NeurIPS 2024Hierarchical Selective Classification
16. NeurIPS 2024Noether's Razor: Learning Conserved Quantities
17. NeurIPS 2024Nonstationary Sparse Spectral Permanental Process
18. NeurIPS 2024Poisson Variational Autoencoder
19. NeurIPS 2024Practical Bayesian Algorithm Execution via Posterior Sampling
20. NeurIPS 2024Quasi-Bayes meets Vines
21. NeurIPS 2024Reparameterization invariance in approximate Bayesian inference
22. NeurIPS 2024Sample-efficient Bayesian Optimisation Using Known Invariances
23. NeurIPS 2024SEL-BALD: Deep Bayesian Active Learning with Selective Labels
24. NeurIPS 2024Set-based Neural Network Encoding Without Weight Tying
25. NeurIPS 2024Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood
26. NeurIPS 2024The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons
27. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
28. NeurIPS 2024Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
29. NeurIPS 2024Unrolled denoising networks provably learn to perform optimal Bayesian inference
30. NeurIPS 2024Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance

常见问题

2023–2026 年四大会议一共有多少篇贝叶斯深度学习论文？

共 408 篇，按年份分别是 2023 年 112 篇、2024 年 100 篇、2025 年 84 篇、2026 年 112 篇。

NeurIPS 2026 有多少篇贝叶斯深度学习论文？

NeurIPS 2026 有 40 篇贝叶斯深度学习论文，上一届是 27 篇。

ICLR 2026 有多少篇贝叶斯深度学习论文？

ICLR 2026 有 22 篇贝叶斯深度学习论文，上一届是 30 篇。

ICML 2026 有多少篇贝叶斯深度学习论文？

ICML 2026 有 41 篇贝叶斯深度学习论文，上一届是 24 篇。

CVPR 2026 有多少篇贝叶斯深度学习论文？

CVPR 2026 有 9 篇贝叶斯深度学习论文，上一届是 3 篇。

哪个会议的贝叶斯深度学习论文最多？

NeurIPS，2023–2026 年共 165 篇。