深度学习 · probabilistic methods论文趋势 2023–2026

ICML/NeurIPS 深度学习方向：probabilistic_methods

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 637 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

深度学习 · probabilistic methods论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023697256107
20241315186160
202521210374263
20262813597107

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

全部深度学习 · probabilistic methods论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 637 篇，第 7 / 13 页

  1. NeurIPS 2025Parallelizing MCMC Across the Sequence Length
  2. NeurIPS 2025Personalized Federated Conformal Prediction with Localization
  3. NeurIPS 2025PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation
  4. NeurIPS 2025Practical Kernel Selection for Kernel-based Conditional Independence Test
  5. NeurIPS 2025Prediction-Powered Causal Inferences
  6. NeurIPS 2025Probabilistic Token Alignment for Large Language Model Fusion
  7. NeurIPS 2025ProDAG: Projected Variational Inference for Directed Acyclic Graphs
  8. NeurIPS 2025PUATE: Efficient ATE Estimation from Treated (Positive) and Unlabeled Units
  9. NeurIPS 2025Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inference
  10. NeurIPS 2025Quantifying Uncertainty in the Presence of Distribution Shifts
  11. NeurIPS 2025Quantitative convergence of trained neural networks to Gaussian processes
  12. NeurIPS 2025Quantum speedup of non-linear Monte Carlo problems
  13. NeurIPS 2025Rao-Blackwellised Reparameterisation Gradients
  14. NeurIPS 2025Recurrent Memory for Online Interdomain Gaussian Processes
  15. NeurIPS 2025Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference
  16. NeurIPS 2025Relaxing partition admissibility in Cluster-DAGs: a causal calculus with arbitrary variable clustering
  17. NeurIPS 2025Resolution of Simpson's paradox via the common cause principle
  18. NeurIPS 2025Rethinking Approximate Gaussian Inference in Classification
  19. NeurIPS 2025Rethinking Losses for Diffusion Bridge Samplers
  20. NeurIPS 2025Reverse Diffusion Sequential Monte Carlo Samplers
  21. NeurIPS 2025Reverse-Annealed Sequential Monte Carlo for Efficient Bayesian Optimal Experiment Design
  22. NeurIPS 2025Reward-oriented Causal Representation Learning
  23. NeurIPS 2025Robust and Computation-Aware Gaussian Processes
  24. NeurIPS 2025Robust Sampling for Active Statistical Inference
  25. NeurIPS 2025Root Cause Analysis of Outliers with Missing Structural Knowledge
  26. NeurIPS 2025Sampling by averaging: A multiscale approach to score estimation
  27. NeurIPS 2025Scalable and adaptive prediction bands with kernel sum-of-squares
  28. NeurIPS 2025Score-Based Diffusion Modeling for Nonparametric Empirical Bayes in Heteroscedastic Gaussian Mixtures
  29. NeurIPS 2025Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
  30. NeurIPS 2025SD-KDE: Score-Debiased Kernel Density Estimation
  31. NeurIPS 2025SimpleStrat: Diversifying Language Model Generation with Stratification
  32. NeurIPS 2025Simulation-Based Inference for Adaptive Experiments
  33. NeurIPS 2025SING: SDE Inference via Natural Gradients
  34. NeurIPS 2025Small Resamples, Sharp Guarantees: Convergence Rates for Resampled Studentized Quantile Estimators
  35. NeurIPS 2025Smooth Sailing: Lipschitz-Driven Uncertainty Quantification for Spatial Associations
  36. NeurIPS 2025Solving and Learning Partial Differential Equations with Variational Q-Exponential Processes
  37. NeurIPS 2025Sparse Gaussian Processes: Structured Approximations and Power-EP Revisited
  38. NeurIPS 2025Spectral Convolutional Conditional Neural Process
  39. NeurIPS 2025Spectral Estimation with Free Decompression
  40. NeurIPS 2025Split Gibbs Discrete Diffusion Posterior Sampling
  41. NeurIPS 2025Squared families are useful conjugate priors
  42. NeurIPS 2025STACI: Spatio-Temporal Aleatoric Conformal Inference
  43. NeurIPS 2025Structural Causal Bandits under Markov Equivalence
  44. NeurIPS 2025Synthetic-powered predictive inference
  45. NeurIPS 2025Temporal-Difference Variational Continual Learning
  46. NeurIPS 2025Test Time Scaling for Neural Processes
  47. NeurIPS 2025The Adaptive Complexity of Minimizing Relative Fisher Information
  48. NeurIPS 2025The Quotient Bayesian Learning Rule
  49. NeurIPS 2025The third pillar of causal analysis? A measurement perspective on causal representations
  50. NeurIPS 2025Towards Identifiability of Hierarchical Temporal Causal Representation Learning

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 查深度学习 · probabilistic methods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": "dl-probabilistic-methods"}

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深度学习 · probabilistic methods论文？
共 637 篇，按年份分别是 2023 年 107 篇、2024 年 160 篇、2025 年 263 篇、2026 年 107 篇。
NeurIPS 2026 有多少篇深度学习 · probabilistic methods论文？
NeurIPS 2026 有 28 篇深度学习 · probabilistic methods论文，上一届是 212 篇。
ICLR 2026 有多少篇深度学习 · probabilistic methods论文？
ICLR 2026 有 13 篇深度学习 · probabilistic methods论文，上一届是 10 篇。
ICML 2026 有多少篇深度学习 · probabilistic methods论文？
ICML 2026 有 59 篇深度学习 · probabilistic methods论文，上一届是 37 篇。
CVPR 2026 有多少篇深度学习 · probabilistic methods论文？
CVPR 2026 有 7 篇深度学习 · probabilistic methods论文，上一届是 4 篇。
哪个会议的深度学习 · probabilistic methods论文最多？
NeurIPS，2023–2026 年共 440 篇。

「深度学习」下的其他主题