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 106 篇，第 1 / 3 页

1. NeurIPS 2026$R^3$: 3D Reconstruction via Relative Regression
2. NeurIPS 20263D Gaussian Splatting within Self-Learned Neural View-Dependent Color Fields
3. NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
4. NeurIPS 2026ACD-GS: Asymmetric Curvature-aware Densification for 3D Gaussian Splatting
5. NeurIPS 2026Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights
6. NeurIPS 2026Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
7. NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
8. NeurIPS 2026Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation
9. NeurIPS 2026Autoregressive Appearance Prediction for 3D Gaussian Avatars
10. NeurIPS 2026BEAST3D: animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
11. NeurIPS 2026Black-box model classification under the discriminative factorization
12. NeurIPS 2026Blur Issue Matters for Thermal Novel View Synthesis: A Floating Gaussian Suppression Approach
13. NeurIPS 2026Can Entry-Wise Clipping Give Spectral Control of Stochastic Gradients?
14. NeurIPS 2026CC-GS: Low-Memory 3D Gaussian Splatting Training via CPU-GPU Block-Wise Context Compositing
15. NeurIPS 2026CELEUS: Certifiable and Efficient LLM Evaluation via E-Processes
16. NeurIPS 2026Coarsening Linear Non-Gaussian Causal Models with Cycles
17. NeurIPS 2026CodecSplat: Ultra-Compact Latent Coding for Feed-Forward 3D Gaussian Splatting
18. NeurIPS 2026Complexity Aware Continuous Level of Details for Gaussian Splatting
19. NeurIPS 2026Complexity-guided Regularization for Generalizable Human Gaussian Splatting
20. NeurIPS 2026Concord-SLAM: Cross-Render Concordance for Boundary-Native Semantic Gaussian SLAM
21. NeurIPS 2026Conditioning Gaussian Processes on Almost Anything
22. NeurIPS 2026Constrained Bombieri Point Processes
23. NeurIPS 2026Continuous-depth Deep Gaussian Processes
24. NeurIPS 2026Corrected Integrated Laplace Approximation for Bayesian Inference in Latent Gaussian Models
25. NeurIPS 2026Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
26. NeurIPS 2026Deep Gaussian Processes on Directed Acyclic Graphs
27. NeurIPS 2026Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes
28. NeurIPS 2026Deformable 2D Gaussian Splatting
29. NeurIPS 2026Diffeomoprhism-Informed 3D Gaussian Splattings via Screen-Space Optimal Transport (OT)
30. NeurIPS 2026Disambiguating 2D-3D Correspondences in Gaussian Splatting-based Feature Fields for Visual Localization
31. NeurIPS 2026DnNP: Denoising Input Uncertainty in Neural Processes
32. NeurIPS 2026DTGS: Physics-Embedded Dynamic Thermal 3D Reconstruction with Gaussian Splatting
33. NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
34. NeurIPS 2026Estimation of the Label-Noise Transition Matrix with Performance Guarantees via Selective Classification
35. NeurIPS 2026Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
36. NeurIPS 2026Feed-Forward 3D Gaussian Splatting for High-Fidelity Animatable Hand Avatar Reconstruction from a Single Image
37. NeurIPS 2026Finite-Sample Performance of Gradient Descent in Logistic Regression with Gaussian Design
38. NeurIPS 2026Flexible Intensities Matter: A comprehensive re-evaluation of Classical and Neural Temporal Point Processes
39. NeurIPS 2026Flow-Transformed Implicit Processes for Function-Space Variational Inference
40. NeurIPS 2026From Jumps to Signatures: a Generative Method for Temporal Point Processes
41. NeurIPS 2026GAMMA: Scalable 4D Gaussian Reconstruction Model for Novel View Synthesis of Monocular Videos
42. NeurIPS 2026GauGal: Gaussian-Galerkin Electromagnetic Inverse Scattering Imaging
43. NeurIPS 2026Gaussian Density Splatting Network
44. NeurIPS 2026Gaussian Mixture Models in Hilbert Spaces via Kernel Methods
45. NeurIPS 2026Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension
46. NeurIPS 2026Geometry-Aware Score-Repellent Monte Carlo
47. NeurIPS 2026GGQR: Gaussian-Grounded Query Refinement for Feed-Forward 4D Gaussian Splatting
48. NeurIPS 2026High-dimensional Gaussian Graphical Model Testing for Long-Memory Time Series
49. NeurIPS 2026How Deep Are Deep GPs, Really? A Sharp Threshold and a Non-Gaussian Limit for Compositional GPs
50. NeurIPS 2026Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point 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。