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

91 papers, page 1 of 2

1. NeurIPS 2024A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
2. NeurIPS 2024Achieving Constant Regret in Linear Markov Decision Processes
3. NeurIPS 2024Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures
4. NeurIPS 2024Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
5. NeurIPS 2024Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
6. NeurIPS 2024Approximately Equivariant Neural Processes
7. NeurIPS 2024Approximation-Aware Bayesian Optimization
8. NeurIPS 2024Batched Energy-Entropy acquisition for Bayesian Optimization
9. NeurIPS 2024Bayesian Adaptive Calibration and Optimal Design
10. NeurIPS 2024Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing
11. NeurIPS 2024Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding
12. NeurIPS 2024Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis
13. NeurIPS 2024Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently
14. NeurIPS 2024Causal Imitation for Markov Decision Processes: a Partial Identification Approach
15. NeurIPS 2024Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
16. NeurIPS 2024Conditioning non-linear and infinite-dimensional diffusion processes
17. NeurIPS 2024Decomposable Transformer Point Processes
18. NeurIPS 2024Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval
19. NeurIPS 2024Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
20. NeurIPS 2024Distributed Sparse Regression via Penalization
21. NeurIPS 2024EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models
22. NeurIPS 2024Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis
23. NeurIPS 2024Event-3DGS: Event-based 3D Reconstruction Using 3D Gaussian Splatting
24. NeurIPS 2024Expressive Gaussian Human Avatars from Monocular RGB Video
25. NeurIPS 2024Finding good policies in average-reward Markov Decision Processes without prior knowledge
26. NeurIPS 2024Flipping-based Policy for Chance-Constrained Markov Decision Processes
27. NeurIPS 2024FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
28. NeurIPS 2024FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
29. NeurIPS 2024Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
30. NeurIPS 2024Gaussian Process Bandits for Top-k Recommendations
31. NeurIPS 2024Generalizable and Animatable Gaussian Head Avatar
32. NeurIPS 2024GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation
33. NeurIPS 2024Gradients of Functions of Large Matrices
34. NeurIPS 2024Graph Neural Networks Do Not Always Oversmooth
35. NeurIPS 2024Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splatting
36. NeurIPS 2024GS-Hider: Hiding Messages into 3D Gaussian Splatting
37. NeurIPS 2024GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction
38. NeurIPS 2024GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes
39. NeurIPS 2024HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems
40. NeurIPS 2024HiCoM: Hierarchical Coherent Motion for Dynamic Streamable Scenes with 3D Gaussian Splatting
41. NeurIPS 2024Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
42. NeurIPS 2024Improving Adaptivity via Over-Parameterization in Sequence Models
43. NeurIPS 2024Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
44. NeurIPS 2024Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition
45. NeurIPS 2024Is Score Matching Suitable for Estimating Point Processes?
46. NeurIPS 2024Kermut: Composite kernel regression for protein variant effects
47. NeurIPS 2024Large Spatial Model: End-to-end Unposed Images to Semantic 3D
48. NeurIPS 2024Learning from Snapshots of Discrete and Continuous Data Streams
49. NeurIPS 2024LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS
50. NeurIPS 2024Linear Regression using Heterogeneous Data Batches

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.