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 64 篇，第 1 / 2 页

1. ICML 2024$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
2. ICML 2024A Rate-Distortion View of Uncertainty Quantification
3. ICML 2024A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
4. ICML 2024Amortized Variational Deep Kernel Learning
5. ICML 2024An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network
6. ICML 2024Asymptotics of feature learning in two-layer networks after one gradient-step
7. ICML 2024Asymptotics of Learning with Deep Structured (Random) Features
8. ICML 2024Autoencoding Conditional Neural Processes for Representation Learning
9. ICML 2024Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
10. ICML 2024Classification Under Strategic Self-Selection
11. ICML 2024Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
12. ICML 2024Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
13. ICML 2024Critical feature learning in deep neural networks
14. ICML 2024Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures
15. ICML 2024Deep Regression Representation Learning with Topology
16. ICML 2024EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
17. ICML 2024Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
18. ICML 2024Efficient Value Iteration for s-rectangular Robust Markov Decision Processes
19. ICML 2024Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
20. ICML 2024EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting
21. ICML 2024First-Order Manifold Data Augmentation for Regression Learning
22. ICML 2024Gaussian Plane-Wave Neural Operator for Electron Density Estimation
23. ICML 2024Gaussian Processes on Cellular Complexes
24. ICML 2024GaussianPro: 3D Gaussian Splatting with Progressive Propagation
25. ICML 2024Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
26. ICML 2024Geometry-Aware Instrumental Variable Regression
27. ICML 2024Guidance with Spherical Gaussian Constraint for Conditional Diffusion
28. ICML 2024Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
29. ICML 2024Interacting Diffusion Processes for Event Sequence Forecasting
30. ICML 2024Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
31. ICML 2024Learning in Deep Factor Graphs with Gaussian Belief Propagation
32. ICML 2024Learning Latent Space Hierarchical EBM Diffusion Models
33. ICML 2024Learning Mixtures of Gaussian Processes through Random Projection
34. ICML 2024Learning to Reach Goals via Diffusion
35. ICML 2024Logistic Variational Bayes Revisited
36. ICML 2024Memory Efficient Neural Processes via Constant Memory Attention Block
37. ICML 2024Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
38. ICML 2024Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
39. ICML 2024Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
40. ICML 2024Neural Jump-Diffusion Temporal Point Processes
41. ICML 2024Neuro-Symbolic Temporal Point Processes
42. ICML 2024No Double Descent in Principal Component Regression: A High-Dimensional Analysis
43. ICML 2024On the Consistency of Kernel Methods with Dependent Observations
44. ICML 2024One-Shot Strategic Classification Under Unknown Costs
45. ICML 2024PAGER: Accurate Failure Characterization in Deep Regression Models
46. ICML 2024Physics and Lie symmetry informed Gaussian processes
47. ICML 2024Preventing Model Collapse in Gaussian Process Latent Variable Models
48. ICML 2024Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes
49. ICML 2024Probabilistic Generating Circuits - Demystified
50. ICML 2024Probabilistic Modeling of Interpersonal Coordination 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。