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
- 高斯过程论文从 2023 年的 154 篇增长到 2026 年的 341 篇，三年间扩大到约 2.2 倍。
- NeurIPS 是发高斯过程论文最多的会议，2023–2026 年共 372 篇，占四个会议总量的 35%。
- 交叉方向里涨得最快的是三维视觉：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 158 篇。
- 在「概率与贝叶斯」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的生成流是 1.9 倍，高斯过程是 2.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 69 | 27 | 48 | 10 | 154 |
| 2024 | 91 | 36 | 64 | 40 | 231 |
| 2025 | 106 | 41 | 53 | 123 | 323 |
| 2026 | 106 | 40 | 79 | 116 | 341 |
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 2026Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
- ICML 2026A unified theory of feature learning in RNNs and DNNs
- ICLR 2026Adaptive Gaussian Expansion for On-the-fly Category Discovery
- CVPR 2026Distilling Unsigned Distance Function for Surface Reconstruction from 3D Gaussian
- NeurIPS 2025Accelerated Evolving Set Processes for Local PageRank Computation
- ICML 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
- ICLR 2025Boosting Methods for Interval-censored Data with Regression and Classification
- CVPR 20253D Gaussian Head Avatars with Expressive Dynamic Appearances by Compact Tensorial Representations
- NeurIPS 2024Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
- ICML 2024A Rate-Distortion View of Uncertainty Quantification
- ICLR 2024A General Framework for User-Guided Bayesian Optimization
- CVPR 2024Deep Imbalanced Regression via Hierarchical Classification Adjustment
- NeurIPS 2023A Bayesian Take on Gaussian Process Networks
- ICML 2023Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation
- ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
- CVPR 2023Robust and Scalable Gaussian Process Regression and Its Applications
- NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
- ICML 2026ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
- ICLR 2026Continuous multinomial logistic regression for neural decoding
- CVPR 2026ELITE Efficient Gaussian Head Avatar from a Monocular Video via
全部高斯过程论文
共 231 篇，第 5 / 5 页
- NeurIPS 2024Non-parametric classification via expand-and-sparsify representation
- NeurIPS 2024Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
- NeurIPS 2024ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings
- NeurIPS 2024On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models
- NeurIPS 2024Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
- NeurIPS 2024Physics-Informed Variational State-Space Gaussian Processes
- NeurIPS 2024Piecewise deterministic generative models
- NeurIPS 2024Pre-trained Gaussian Processes for Bayesian Optimization
- NeurIPS 2024R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
- NeurIPS 2024Random Function Descent
- NeurIPS 2024ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting
- NeurIPS 2024Reliable Learning of Halfspaces under Gaussian Marginals
- NeurIPS 2024Robust Gaussian Processes via Relevance Pursuit
- NeurIPS 2024Robust Sparse Regression with Non-Isotropic Designs
- NeurIPS 2024Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
- NeurIPS 2024Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
- NeurIPS 2024Sample-efficient Bayesian Optimisation Using Known Invariances
- NeurIPS 2024Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
- NeurIPS 2024Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
- NeurIPS 2024Slight Corruption in Pre-training Data Makes Better Diffusion Models
- NeurIPS 2024Small coresets via negative dependence: DPPs, linear statistics, and concentration
- NeurIPS 2024Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting
- NeurIPS 2024Spectral Learning of Shared Dynamics Between Generalized-Linear Processes
- NeurIPS 2024Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
- NeurIPS 2024Stopping Bayesian Optimization with Probabilistic Regret Bounds
- NeurIPS 2024The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems
- NeurIPS 2024Truncated Variance Reduced Value Iteration
- NeurIPS 2024Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
- NeurIPS 2024Universality in Transfer Learning for Linear Models
- NeurIPS 2024VCR-GauS: View Consistent Depth-Normal Regularizer for Gaussian Surface Reconstruction
- NeurIPS 2024WildGaussians: 3D Gaussian Splatting In the Wild
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"}
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。