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

372 papers, page 5 of 8

201. NeurIPS 2025Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
202. NeurIPS 2025Temporal Smoothness-Aware Rate-Distortion Optimized 4D Gaussian Splatting
203. NeurIPS 2025The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model
204. NeurIPS 2025The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
205. NeurIPS 2025The Generative Leap: Tight Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
206. NeurIPS 2025The Quest for Universal Master Key Filters in DS-CNNs
207. NeurIPS 2025Transformers are almost optimal metalearners for linear classification
208. NeurIPS 2025TreeSplat: Mergeable Tree for Deformable Gaussian Splatting
209. NeurIPS 2025TRIM: Scalable 3D Gaussian Diffusion Inference with Temporal and Spatial Trimming
210. NeurIPS 2025Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
211. NeurIPS 2025VA-GS: Enhancing the Geometric Representation of Gaussian Splatting via View Alignment
212. NeurIPS 2025Zero-Shot Performance Prediction for Probabilistic Scaling Laws
213. NeurIPS 2024A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
214. NeurIPS 2024Achieving Constant Regret in Linear Markov Decision Processes
215. NeurIPS 2024Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures
216. NeurIPS 2024Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
217. NeurIPS 2024Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
218. NeurIPS 2024Approximately Equivariant Neural Processes
219. NeurIPS 2024Approximation-Aware Bayesian Optimization
220. NeurIPS 2024Batched Energy-Entropy acquisition for Bayesian Optimization
221. NeurIPS 2024Bayesian Adaptive Calibration and Optimal Design
222. NeurIPS 2024Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing
223. NeurIPS 2024Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding
224. NeurIPS 2024Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis
225. NeurIPS 2024Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
226. NeurIPS 2024Causal Imitation for Markov Decision Processes: a Partial Identification Approach
227. NeurIPS 2024Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
228. NeurIPS 2024Conditioning non-linear and infinite-dimensional diffusion processes
229. NeurIPS 2024Decomposable Transformer Point Processes
230. NeurIPS 2024Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval
231. NeurIPS 2024Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
232. NeurIPS 2024Distributed Sparse Regression via Penalization
233. NeurIPS 2024EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models
234. NeurIPS 2024Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis
235. NeurIPS 2024Event-3DGS: Event-based 3D Reconstruction Using 3D Gaussian Splatting
236. NeurIPS 2024Expressive Gaussian Human Avatars from Monocular RGB Video
237. NeurIPS 2024Finding good policies in average-reward Markov Decision Processes without prior knowledge
238. NeurIPS 2024Flipping-based Policy for Chance-Constrained Markov Decision Processes
239. NeurIPS 2024FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
240. NeurIPS 2024FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
241. NeurIPS 2024Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
242. NeurIPS 2024Gaussian Process Bandits for Top-k Recommendations
243. NeurIPS 2024Generalizable and Animatable Gaussian Head Avatar
244. NeurIPS 2024GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation
245. NeurIPS 2024Gradients of Functions of Large Matrices
246. NeurIPS 2024Graph Neural Networks Do Not Always Oversmooth
247. NeurIPS 2024Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splatting
248. NeurIPS 2024GS-Hider: Hiding Messages into 3D Gaussian Splatting
249. NeurIPS 2024GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction
250. NeurIPS 2024GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes

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.