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

每年论文数

各会议论文数

按年份和会议统计

高斯过程论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202369274810154
202491366440231
20251064153123323
20261064079116341

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

全部高斯过程论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,049 篇，第 5 / 21 页

  1. ICML 2026Local Constrained Bayesian Optimization
  2. ICML 2026Local Policies for Graph-Structured Markov Decision Processes
  3. ICML 2026Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
  4. ICML 2026Monotonic Variational Gaussian Process for Efficient Data Collection
  5. ICML 2026Networked Information Aggregation for Binary Classification
  6. ICML 2026Nonparametric Distribution Regression Re-calibration
  7. ICML 2026On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise
  8. ICML 2026PCGS: Deblurring 3D Gaussian Splatting with Patch Comparison
  9. ICML 2026Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
  10. ICML 2026Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces
  11. ICML 2026Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
  12. ICML 2026Probabilistically-routed Bayesian Additive Spanning Trees for Learning on Constrained Domains
  13. ICML 2026ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
  14. ICML 2026Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
  15. ICML 2026Reconstruction Outcomes Look Similar but Processes Differ: Improving Context Consistency and Coverage in Graph Masked Auto-Encoder
  16. ICML 2026Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
  17. ICML 2026Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction
  18. ICML 2026Richer Bayesian Last Layers with Subsampled NTK Features
  19. ICML 2026S2GS: Streaming Semantic Gaussian Splatting for Online Scene Understanding and Reconstruction
  20. ICML 2026Scalable Bayesian Inference for Nonlinear Conservation Laws
  21. ICML 2026SE(3)-Equivariant Flow Matching with Gaussian Process Priors for Geometric Trajectory Prediction
  22. ICML 2026Sharp Concentration Bounds for Bundle-Valued Statistics on Manifolds
  23. ICML 2026Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
  24. ICML 2026Signal Strength Estimation in Logistic Regression Using Data Splitting
  25. ICML 2026SIKA-GP: Accelerating Gaussian Process Inference with Sparse Inducing Kernel Approximations for Bayesian Deep Learning
  26. ICML 2026Sparse Regression with $\ell_0$ Constraints for $\alpha$-Mixing Time Series: Algorithms and Guarantees
  27. ICML 2026Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments
  28. ICML 2026Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
  29. ICML 2026Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
  30. ICML 2026The Value Function Semi-Algebraic Set in Partially Observable Markov Decision Processes
  31. ICML 2026TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
  32. ICML 2026Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere
  33. ICML 2026Token Sample Complexity of Attention
  34. ICML 2026Transformed Latent Variable Multi-Output Gaussian Processes
  35. ICML 2026Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
  36. NeurIPS 2026$R^3$: 3D Reconstruction via Relative Regression
  37. NeurIPS 20263D Gaussian Splatting within Self-Learned Neural View-Dependent Color Fields
  38. NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
  39. NeurIPS 2026ACD-GS: Asymmetric Curvature-aware Densification for 3D Gaussian Splatting
  40. NeurIPS 2026Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights
  41. NeurIPS 2026Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
  42. NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
  43. NeurIPS 2026Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation
  44. NeurIPS 2026Autoregressive Appearance Prediction for 3D Gaussian Avatars
  45. NeurIPS 2026BEAST3D: animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
  46. NeurIPS 2026Black-box model classification under the discriminative factorization
  47. NeurIPS 2026Blur Issue Matters for Thermal Novel View Synthesis: A Floating Gaussian Suppression Approach
  48. NeurIPS 2026Can Entry-Wise Clipping Give Spectral Control of Stochastic Gradients?
  49. NeurIPS 2026CC-GS: Low-Memory 3D Gaussian Splatting Training via CPU-GPU Block-Wise Context Compositing
  50. NeurIPS 2026CELEUS: Certifiable and Efficient LLM Evaluation via E-Processes

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

「概率与贝叶斯」下的其他主题