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 144 篇，第 1 / 3 页

1. ICLR 2026A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization
2. ICLR 2026A Statistical Theory of Overfitting for Imbalanced Classification
3. ICLR 2026A Unification of Discrete, Gaussian, and Simplicial Diffusion
4. ICLR 2026Active Learning of 3D Gaussian Splatting with Consistent Region Partition and Robust Pose Estimation
5. ICLR 2026Adaptive Gaussian Expansion for On-the-fly Category Discovery
6. ICLR 2026All That Glitters Is Not Gold: Key-Secured 3D Secrets within 3D Gaussian Splatting
7. ICLR 2026An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes
8. ICLR 2026Bayesian Parameter Shift Rules in Variational Quantum Eigensolvers
9. ICLR 2026Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes
10. ICLR 2026Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks
11. ICLR 2026CompMarkGS: Robust Watermarking for Compressed 3D Gaussian Splatting
12. ICLR 2026Continuous multinomial logistic regression for neural decoding
13. ICLR 2026Cooperative Sheaf Neural Networks
14. ICLR 2026CryoSplat: Gaussian Splatting for Cryo-EM Homogeneous Reconstruction
15. ICLR 2026DeNOTS: Stable Deep Neural ODEs for Time Series
16. ICLR 2026Diffusion Bridge Variational Inference for Deep Gaussian Processes
17. ICLR 2026Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning
18. ICLR 2026Edit-Based Flow Matching for Temporal Point Processes
19. ICLR 2026Fair Graph Machine Learning under Adversarial Missingness Processes
20. ICLR 2026Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances
21. ICLR 2026Frequency-aware Dynamic Gaussian Splatting
22. ICLR 2026Gaussian certified unlearning in high dimensions: A hypothesis testing approach
23. ICLR 2026Gradient-Direction-Aware Density Control for 3D Gaussian Splatting
24. ICLR 2026Graph Random Features for Scalable Gaussian Processes
25. ICLR 2026Horseshoe Splatting: Handling Structural Sparsity for Uncertainty-Aware Gaussian-Splatting Radiance Field Rendering
26. ICLR 2026In-Context Learning of Temporal Point Processes with Foundation Inference Models
27. ICLR 2026Incorporating Expert Priors into Bayesian Optimization via Dynamic Mean Decay
28. ICLR 2026InfoNCE Induces Gaussian Distribution
29. ICLR 2026Learning Unified Representation of 3D Gaussian Splatting
30. ICLR 2026Meta-Learning Theory-Informed Inductive Biases using Deep Kernel Gaussian Processes
31. ICLR 2026Multiplicative Diffusion Models: Beyond Gaussian Latents
32. ICLR 2026Rethinking Pareto Frontier: On the Optimal Trade-offs in Fair Classification
33. ICLR 2026Revisiting Nonstationary Kernel Design for Multi-Output Gaussian Processes
34. ICLR 2026Robust Generalized Schr\"{o}dinger Bridge via Sparse Variational Gaussian Processes
35. ICLR 2026Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees
36. ICLR 2026Slicing Wasserstein over Wasserstein via Functional Optimal Transport
37. ICLR 2026Splat Regression Models
38. ICLR 2026station2radar: query‑conditioned gaussian splatting for precipitation field
39. ICLR 2026The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics
40. ICLR 2026Transformers as Unsupervised Learning Algorithms: A study on Gaussian Mixtures
41. ICLR 20256DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering
42. ICLR 2025Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes
43. ICLR 2025Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
44. ICLR 2025Bayesian Analysis of Combinatorial Gaussian Process Bandits
45. ICLR 2025Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution
46. ICLR 2025Boosting Methods for Interval-censored Data with Regression and Classification
47. ICLR 2025Deep Kernel Posterior Learning under Infinite Variance Prior Weights
48. ICLR 2025Deep Random Features for Scalable Interpolation of Spatiotemporal Data
49. ICLR 2025Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
50. ICLR 2025Dimension Agnostic Neural 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。