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 323 篇，第 4 / 7 页

  1. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
  2. ICLR 2025Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
  3. ICLR 2025Poison-splat: Computation Cost Attack on 3D Gaussian Splatting
  4. ICLR 2025ReMatching Dynamic Reconstruction Flow
  5. ICLR 2025Residual Deep Gaussian Processes on Manifolds
  6. ICLR 2025Robust Simulation-Based Inference under Missing Data via Neural Processes
  7. ICLR 2025SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography
  8. ICLR 2025Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
  9. ICLR 2025Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
  10. ICLR 2025Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
  11. ICLR 2025SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars
  12. ICLR 2025The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures
  13. ICLR 2025Unlocking Point Processes through Point Set Diffusion
  14. ICLR 2025Variance-Reducing Couplings for Random Features
  15. ICML 2025Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
  16. ICML 2025BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
  17. ICML 2025Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
  18. ICML 2025Determinant Estimation under Memory Constraints and Neural Scaling Laws
  19. ICML 2025Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
  20. ICML 2025Distributionally Robust Active Learning for Gaussian Process Regression
  21. ICML 2025Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
  22. ICML 2025Feature learning from non-Gaussian inputs: the case of Independent Component Analysis in high dimensions
  23. ICML 2025Finite-Time Analysis of Discrete-Time Stochastic Interpolants
  24. ICML 2025Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
  25. ICML 2025Global Optimization with a Power-Transformed Objective and Gaussian Smoothing
  26. ICML 2025Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables
  27. ICML 2025Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
  28. ICML 2025Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
  29. ICML 2025Gridded Transformer Neural Processes for Spatio-Temporal Data
  30. ICML 2025Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
  31. ICML 2025Integration-free Kernels for Equivariant Gaussian Process Modelling
  32. ICML 2025Interaction-Aware Gaussian Weighting for Clustered Federated Learning
  33. ICML 2025K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
  34. ICML 2025Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
  35. ICML 2025Learning Gaussian DAG Models without Condition Number Bounds
  36. ICML 2025Learning multivariate Gaussians with imperfect advice
  37. ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
  38. ICML 2025Learning Safe Control via On-the-Fly Bandit Exploration
  39. ICML 2025Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
  40. ICML 2025Learning Utilities from Demonstrations in Markov Decision Processes
  41. ICML 2025Linearization Turns Neural Operators into Function-Valued Gaussian Processes
  42. ICML 2025Low-Rank Thinning
  43. ICML 2025Model-Based Exploration in Monitored Markov Decision Processes
  44. ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
  45. ICML 2025New Bounds for Sparse Variational Gaussian Processes
  46. ICML 2025On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
  47. ICML 2025PAC-Bayes Analysis for Recalibration in Classification
  48. ICML 2025Pareto-frontier Entropy Search with Variational Lower Bound Maximization
  49. ICML 2025PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis
  50. ICML 2025PRIME: Deep Imbalanced Regression with Proxies

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。

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