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 244 篇，第 3 / 5 页

101. ICML 2025Learning multivariate Gaussians with imperfect advice
102. ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
103. ICML 2025Learning Safe Control via On-the-Fly Bandit Exploration
104. ICML 2025Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
105. ICML 2025Learning Utilities from Demonstrations in Markov Decision Processes
106. ICML 2025Linearization Turns Neural Operators into Function-Valued Gaussian Processes
107. ICML 2025Low-Rank Thinning
108. ICML 2025Model-Based Exploration in Monitored Markov Decision Processes
109. ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
110. ICML 2025New Bounds for Sparse Variational Gaussian Processes
111. ICML 2025On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
112. ICML 2025PAC-Bayes Analysis for Recalibration in Classification
113. ICML 2025Pareto-frontier Entropy Search with Variational Lower Bound Maximization
114. ICML 2025PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis
115. ICML 2025PRIME: Deep Imbalanced Regression with Proxies
116. ICML 2025Quantum Algorithms for Finite-horizon Markov Decision Processes
117. ICML 2025Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
118. ICML 2025Rényi Neural Processes
119. ICML 2025Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
120. ICML 2025Robust and Conjugate Spatio-Temporal Gaussian Processes
121. ICML 2025Sample Complexity of Correlation Detection in the Gaussian Wigner Model
122. ICML 2025Scalable Gaussian Processes with Latent Kronecker Structure
123. ICML 2025Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo
124. ICML 2025Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization
125. ICML 2025Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise
126. ICML 2025Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
127. ICML 2025Stream-level Flow Matching with Gaussian Processes
128. ICML 2025The Price of Linear Time: Error Analysis of Structured Kernel Interpolation
129. ICML 2025Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
130. ICML 2025Trajectory Inference with Smooth Schrödinger Bridges
131. ICML 2025Universal Approximation Theorem of Deep Q-Networks
132. ICML 2025Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
133. ICML 2024$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
134. ICML 2024A Rate-Distortion View of Uncertainty Quantification
135. ICML 2024A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
136. ICML 2024Amortized Variational Deep Kernel Learning
137. ICML 2024An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network
138. ICML 2024Asymptotics of feature learning in two-layer networks after one gradient-step
139. ICML 2024Asymptotics of Learning with Deep Structured (Random) Features
140. ICML 2024Autoencoding Conditional Neural Processes for Representation Learning
141. ICML 2024Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
142. ICML 2024Classification Under Strategic Self-Selection
143. ICML 2024Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
144. ICML 2024Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
145. ICML 2024Critical feature learning in deep neural networks
146. ICML 2024Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures
147. ICML 2024Deep Regression Representation Learning with Topology
148. ICML 2024EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
149. ICML 2024Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
150. ICML 2024Efficient Value Iteration for s-rectangular Robust Markov Decision 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。