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

341 papers, page 6 of 7

251. NeurIPS 2026Coarsening Linear Non-Gaussian Causal Models with Cycles
252. NeurIPS 2026CodecSplat: Ultra-Compact Latent Coding for Feed-Forward 3D Gaussian Splatting
253. NeurIPS 2026Complexity Aware Continuous Level of Details for Gaussian Splatting
254. NeurIPS 2026Complexity-guided Regularization for Generalizable Human Gaussian Splatting
255. NeurIPS 2026Concord-SLAM: Cross-Render Concordance for Boundary-Native Semantic Gaussian SLAM
256. NeurIPS 2026Conditioning Gaussian Processes on Almost Anything
257. NeurIPS 2026Constrained Bombieri Point Processes
258. NeurIPS 2026Continuous-depth Deep Gaussian Processes
259. NeurIPS 2026Corrected Integrated Laplace Approximation for Bayesian Inference in Latent Gaussian Models
260. NeurIPS 2026Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
261. NeurIPS 2026Deep Gaussian Processes on Directed Acyclic Graphs
262. NeurIPS 2026Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes
263. NeurIPS 2026Deformable 2D Gaussian Splatting
264. NeurIPS 2026Diffeomoprhism-Informed 3D Gaussian Splattings via Screen-Space Optimal Transport (OT)
265. NeurIPS 2026Disambiguating 2D-3D Correspondences in Gaussian Splatting-based Feature Fields for Visual Localization
266. NeurIPS 2026DnNP: Denoising Input Uncertainty in Neural Processes
267. NeurIPS 2026DTGS: Physics-Embedded Dynamic Thermal 3D Reconstruction with Gaussian Splatting
268. NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
269. NeurIPS 2026Estimation of the Label-Noise Transition Matrix with Performance Guarantees via Selective Classification
270. NeurIPS 2026Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
271. NeurIPS 2026Feed-Forward 3D Gaussian Splatting for High-Fidelity Animatable Hand Avatar Reconstruction from a Single Image
272. NeurIPS 2026Finite-Sample Performance of Gradient Descent in Logistic Regression with Gaussian Design
273. NeurIPS 2026Flexible Intensities Matter: A comprehensive re-evaluation of Classical and Neural Temporal Point Processes
274. NeurIPS 2026Flow-Transformed Implicit Processes for Function-Space Variational Inference
275. NeurIPS 2026From Jumps to Signatures: a Generative Method for Temporal Point Processes
276. NeurIPS 2026GAMMA: Scalable 4D Gaussian Reconstruction Model for Novel View Synthesis of Monocular Videos
277. NeurIPS 2026GauGal: Gaussian-Galerkin Electromagnetic Inverse Scattering Imaging
278. NeurIPS 2026Gaussian Density Splatting Network
279. NeurIPS 2026Gaussian Mixture Models in Hilbert Spaces via Kernel Methods
280. NeurIPS 2026Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension
281. NeurIPS 2026Geometry-Aware Score-Repellent Monte Carlo
282. NeurIPS 2026GGQR: Gaussian-Grounded Query Refinement for Feed-Forward 4D Gaussian Splatting
283. NeurIPS 2026High-dimensional Gaussian Graphical Model Testing for Long-Memory Time Series
284. NeurIPS 2026How Deep Are Deep GPs, Really? A Sharp Threshold and a Non-Gaussian Limit for Compositional GPs
285. NeurIPS 2026Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point Processes
286. NeurIPS 2026Learning Hierarchical Forward Processes For Discrete Diffusion Language Models
287. NeurIPS 2026LLM Flow Processes for Text-Conditioned Regression
288. NeurIPS 2026Local Gaussian Processes on Compact Lie Groups
289. NeurIPS 2026Local linear convergence of gradient methods for overparameterized Gaussian mixtures
290. NeurIPS 2026Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields
291. NeurIPS 2026MCSplat: Multi-View Photometric and Geometric Consistent Feed-Forward Gaussian Splatting for Driving Scenes
292. NeurIPS 2026Mesh Invaiant Infinite Dimensional Adaptive MCMC for Latent Gaussian Processes
293. NeurIPS 2026Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification
294. NeurIPS 2026MOCHA: Discovering Multi-Order Dynamic Causal Structure in Temporal Point Processes
295. NeurIPS 2026Model-Agnostic FDR Control via Group Gaussian Mirror and Permutation SHAP
296. NeurIPS 2026Multiclass Classification with Rare Useful Features: Fundamental Limits and the Optimality of Diversity Pursuit Higher Criticism
297. NeurIPS 2026MVPISplat: Multi-View Photometric Inconsistency for Defending 3D Gaussian Splatting Attacks
298. NeurIPS 2026Neural Backward Filtering Forward Guiding
299. NeurIPS 2026NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splatting
300. NeurIPS 2026One Avatar, Any Budget: Robust LoD for Dynamic Gaussian Avatars

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.