高斯过程论文趋势 2023–2026

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。

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 36 篇，第 1 / 1 页

1. ICLR 2024A General Framework for User-Guided Bayesian Optimization
2. ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
3. ICLR 2024A Unified Framework for Bayesian Optimization under Contextual Uncertainty
4. ICLR 2024Amortized Network Intervention to Steer the Excitatory Point Processes
5. ICLR 2024Augmented Bayesian Policy Search
6. ICLR 2024Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
7. ICLR 2024Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
8. ICLR 2024Conformal Prediction via Regression-as-Classification
9. ICLR 2024Convolutional Deep Kernel Machines
10. ICLR 2024DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS
11. ICLR 2024EasyTPP: Towards Open Benchmarking Temporal Point Processes
12. ICLR 2024Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
13. ICLR 2024Function-space Parameterization of Neural Networks for Sequential Learning
14. ICLR 2024Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
15. ICLR 2024GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors
16. ICLR 2024Graphical Multioutput Gaussian Process with Attention
17. ICLR 2024Grokking as a First Order Phase Transition in Two Layer Networks
18. ICLR 2024High-dimensional SGD aligns with emerging outlier eigenspaces
19. ICLR 2024HoloNets: Spectral Convolutions do extend to Directed Graphs
20. ICLR 2024Horizon-Free Regret for Linear Markov Decision Processes
21. ICLR 2024Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
22. ICLR 2024Kalman Filter for Online Classification of Non-Stationary Data
23. ICLR 2024Leave-one-out Distinguishability in Machine Learning
24. ICLR 2024Light Schrödinger Bridge
25. ICLR 2024Making Pre-trained Language Models Great on Tabular Prediction
26. ICLR 2024Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes
27. ICLR 2024Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
28. ICLR 2024On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
29. ICLR 2024Optimal Sample Complexity for Average Reward Markov Decision Processes
30. ICLR 2024Prediction Error-based Classification for Class-Incremental Learning
31. ICLR 2024Robust Classification via Regression for Learning with Noisy Labels
32. ICLR 2024Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
33. ICLR 2024Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
34. ICLR 2024Stochastic Gradient Descent for Gaussian Processes Done Right
35. ICLR 2024Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
36. ICLR 2024Uncertainty Quantification via Stable Distribution Propagation

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。