贝叶斯深度学习论文趋势 2023–2026

权重不确定性

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 408 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

贝叶斯深度学习论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
20236819196112
20243026377100
2025273024384
20264022419112

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

全部贝叶斯深度学习论文

共 40 篇,第 1 / 1 页

  1. NeurIPS 2026A Revisit of Hamiltonian Monte Carlo Efficiency on Bayesian Neural Networks
  2. NeurIPS 2026Approximate Bayesian inference with exchangeable distributions for neurosymbolic AI
  3. NeurIPS 2026Bayes-pFCL:Bayesian Personalized Federated Continual Learning
  4. NeurIPS 2026Bayesian Causal Experimental Design for CATE Estimation under Noncompliance
  5. NeurIPS 2026Bayesian Causal Stress Testing: Posterior Fragility of Treatment-Effect Conclusions
  6. NeurIPS 2026Bayesian Low-Rank Posteriors for Scalable Membership Inference
  7. NeurIPS 2026Bayesian Preference Learning for Test-Time Steerable Reward Models
  8. NeurIPS 2026Bifurcation Models: Learning Set-Valued Solution Maps with Weight-Tied Dynamics
  9. NeurIPS 2026BO-Arena: An Evolving Benchmark for High-Dimensional Bayesian Optimisation
  10. NeurIPS 2026CLEAR: Complementary Tripartite Play with Bayesian Calibration for Semi-Supervised Edge Classification
  11. NeurIPS 2026CLUE: Correlated Latent Uncertainty for Single-Pass Deep Uncertainty Estimation
  12. NeurIPS 2026DnNP: Denoising Input Uncertainty in Neural Processes
  13. NeurIPS 2026Does Weight Decay Enhance Training Stability?
  14. NeurIPS 2026DT-PBO: an Interpretable Tree-based Surrogate Model for Preferential Bayesian Optimization
  15. NeurIPS 2026Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference
  16. NeurIPS 2026Ensemble Distributionally Robust Bayesian Optimisation
  17. NeurIPS 2026ESS-Flow: training-free guidance as Bayesian inference in source space
  18. NeurIPS 2026Extrapolative Weight Averaging Reveals Correctness–Efficiency Frontiers in Code RL
  19. NeurIPS 2026Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions
  20. NeurIPS 2026Generative Active Learning via Bayesian Acquisition for Improving the Efficiency of Synthetic Data
  21. NeurIPS 2026Incorporating Neural Network Structure in the Bayesian Learning Rule
  22. NeurIPS 2026Maximin Robust Bayesian Experimental Design
  23. NeurIPS 2026Neural Bayesian Filtering
  24. NeurIPS 2026On the Complexity of Discounted Robust MDPs with $L_p$ Uncertainty Sets
  25. NeurIPS 2026On the Construction and Implications of Low-Loss Valleys in LoRA-based Bayesian Inference
  26. NeurIPS 2026On the Existence of Uniformly Optimal Policies in MDPs under Epistemic Uncertainty
  27. NeurIPS 2026Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
  28. NeurIPS 2026Position: Semantic Uncertainty Measures Disagreement, Not Reliability
  29. NeurIPS 2026Preconditioned Implicit Midpoint Langevin Sampling for Non-Smooth Bayesian Imaging
  30. NeurIPS 2026PRIM: Meta-Learned Bayesian Root Cause Analysis
  31. NeurIPS 2026Proper Scoring Rules for Agentic Uncertainty Quantification
  32. NeurIPS 2026Rethinking Bayesian Optimization for Co-Optimizing LLM Training Configurations
  33. NeurIPS 2026Robust Latent Space Bayesian Optimization with Marginalized Kernel
  34. NeurIPS 2026SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference
  35. NeurIPS 2026TabK: Amortized Bayesian Estimation of the Number of Clusters in Tabular Data
  36. NeurIPS 2026Task-Driven Bayesian Experimental Design Yields Singly Intractable Objectives for Joint Policy Training
  37. NeurIPS 2026The Bayesian Learning Rule Beyond KL Geometry
  38. NeurIPS 2026The Bayesian Origin of the Probability Weighting Function in Human Representation of Probabilities
  39. NeurIPS 2026To discretize continually: Mean shift interacting particle systems for Bayesian inference
  40. NeurIPS 2026Very Fast Bayesian Additive Regression Trees on GPU

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查贝叶斯深度学习在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "bayesian-deep-learning"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

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。

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