高斯过程论文趋势 2023–2026

GP 回归与分类

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,049 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

高斯过程论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202369274810154
202491366440231
20251064153123323
20261064079116341

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

全部高斯过程论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,049 篇，第 19 / 21 页

  1. CVPR 2023Robust and Scalable Gaussian Process Regression and Its Applications
  2. CVPR 2023Single Image Depth Prediction Made Better: A Multivariate Gaussian Take
  3. CVPR 2023Sparsely Annotated Semantic Segmentation With Adaptive Gaussian Mixtures
  4. CVPR 2023Tangentially Elongated Gaussian Belief Propagation for Event-Based Incremental Optical Flow Estimation
  5. CVPR 2023TRACE: 5D Temporal Regression of Avatars With Dynamic Cameras in 3D Environments
  6. ICLR 2023A Kernel Perspective of Skip Connections in Convolutional Networks
  7. ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
  8. ICLR 2023Autoregressive Conditional Neural Processes
  9. ICLR 2023Bridge the Inference Gaps of Neural Processes via Expectation Maximization
  10. ICLR 2023Calibrating Transformers via Sparse Gaussian Processes
  11. ICLR 2023Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?
  12. ICLR 2023Deep Variational Implicit Processes
  13. ICLR 2023Gradient Boosting Performs Gaussian Process Inference
  14. ICLR 2023Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning
  15. ICLR 2023Gray-Box Gaussian Processes for Automated Reinforcement Learning
  16. ICLR 2023Improving Deep Regression with Ordinal Entropy
  17. ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
  18. ICLR 2023Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
  19. ICLR 2023Latent Bottlenecked Attentive Neural Processes
  20. ICLR 2023Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
  21. ICLR 2023Learning Label Encodings for Deep Regression
  22. ICLR 2023Martingale Posterior Neural Processes
  23. ICLR 2023Meta Temporal Point Processes
  24. ICLR 2023Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction
  25. ICLR 2023Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
  26. ICLR 2023Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
  27. ICLR 2023Semi-Parametric Inducing Point Networks and Neural Processes
  28. ICLR 2023SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
  29. ICLR 2023Spatio-temporal point processes with deep non-stationary kernels
  30. ICLR 2023Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning
  31. ICLR 2023Versatile Neural Processes for Learning Implicit Neural Representations
  32. ICLR 2023VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis
  33. ICML 2023A Closer Look at Few-shot Classification Again
  34. ICML 2023Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation
  35. ICML 2023Cluster-Specific Predictions with Multi-Task Gaussian Processes
  36. ICML 2023Communication-Constrained Bandits under Additive Gaussian Noise
  37. ICML 2023Computational Asymmetries in Robust Classification
  38. ICML 2023Continual Learning in Linear Classification on Separable Data
  39. ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
  40. ICML 2023Deep Regression Unlearning
  41. ICML 2023Demystifying Disagreement-on-the-Line in High Dimensions
  42. ICML 2023Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification
  43. ICML 2023FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels
  44. ICML 2023Free-Form Variational Inference for Gaussian Process State-Space Models
  45. ICML 2023Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes
  46. ICML 2023Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
  47. ICML 2023Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
  48. ICML 2023High Probability Convergence of Stochastic Gradient Methods
  49. ICML 2023Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes
  50. ICML 2023Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds

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 查高斯过程在 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": "gaussian-processes"}

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高斯过程论文？
共 1,049 篇，按年份分别是 2023 年 154 篇、2024 年 231 篇、2025 年 323 篇、2026 年 341 篇。
NeurIPS 2026 有多少篇高斯过程论文？
NeurIPS 2026 有 106 篇高斯过程论文，上一届是 106 篇。
ICLR 2026 有多少篇高斯过程论文？
ICLR 2026 有 40 篇高斯过程论文，上一届是 41 篇。
ICML 2026 有多少篇高斯过程论文？
ICML 2026 有 79 篇高斯过程论文，上一届是 53 篇。
CVPR 2026 有多少篇高斯过程论文？
CVPR 2026 有 116 篇高斯过程论文，上一届是 123 篇。
哪个会议的高斯过程论文最多？
NeurIPS，2023–2026 年共 372 篇。

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