Gaussian Processes papers, 2023–2026

Key findings

• Gaussian Processes went from 154 papers in 2023 to 341 in 2026, roughly 2.2x in three years.
• NeurIPS publishes the most Gaussian Processes work: 372 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with 3D Vision: papers tagged with both rose from 0 in 2023 to 158 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #1 by 2026 paper count; the fastest grower in the group, Generative Flows, is up 1.9x versus 2.2x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Gaussian Processes papers

244 papers, page 3 of 5

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

FAQ

How many Gaussian Processes papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,049 in total: 154 in 2023, 231 in 2024, 323 in 2025, 341 in 2026.

How many Gaussian Processes papers are at NeurIPS 2026?

NeurIPS 2026 has 106 Gaussian Processes papers, versus 106 the year before.

How many Gaussian Processes papers are at ICLR 2026?

ICLR 2026 has 40 Gaussian Processes papers, versus 41 the year before.

How many Gaussian Processes papers are at ICML 2026?

ICML 2026 has 79 Gaussian Processes papers, versus 53 the year before.

How many Gaussian Processes papers are at CVPR 2026?

CVPR 2026 has 116 Gaussian Processes papers, versus 123 the year before.

Which conference publishes the most Gaussian Processes papers?

NeurIPS, with 372 papers from 2023 to 2026.