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

1,049 papers, page 5 of 21

201. ICML 2026Local Constrained Bayesian Optimization
202. ICML 2026Local Policies for Graph-Structured Markov Decision Processes
203. ICML 2026Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
204. ICML 2026Monotonic Variational Gaussian Process for Efficient Data Collection
205. ICML 2026Networked Information Aggregation for Binary Classification
206. ICML 2026Nonparametric Distribution Regression Re-calibration
207. ICML 2026On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise
208. ICML 2026PCGS: Deblurring 3D Gaussian Splatting with Patch Comparison
209. ICML 2026Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
210. ICML 2026Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces
211. ICML 2026Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
212. ICML 2026Probabilistically-routed Bayesian Additive Spanning Trees for Learning on Constrained Domains
213. ICML 2026ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
214. ICML 2026Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
215. ICML 2026Reconstruction Outcomes Look Similar but Processes Differ: Improving Context Consistency and Coverage in Graph Masked Auto-Encoder
216. ICML 2026Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
217. ICML 2026Revisiting Photometric Ambiguity for Accurate Gaussian-Splatting Surface Reconstruction
218. ICML 2026Richer Bayesian Last Layers with Subsampled NTK Features
219. ICML 2026S2GS: Streaming Semantic Gaussian Splatting for Online Scene Understanding and Reconstruction
220. ICML 2026Scalable Bayesian Inference for Nonlinear Conservation Laws
221. ICML 2026SE(3)-Equivariant Flow Matching with Gaussian Process Priors for Geometric Trajectory Prediction
222. ICML 2026Sharp Concentration Bounds for Bundle-Valued Statistics on Manifolds
223. ICML 2026Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
224. ICML 2026Signal Strength Estimation in Logistic Regression Using Data Splitting
225. ICML 2026SIKA-GP: Accelerating Gaussian Process Inference with Sparse Inducing Kernel Approximations for Bayesian Deep Learning
226. ICML 2026Sparse Regression with $\ell_0$ Constraints for $\alpha$-Mixing Time Series: Algorithms and Guarantees
227. ICML 2026Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments
228. ICML 2026Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
229. ICML 2026Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
230. ICML 2026The Value Function Semi-Algebraic Set in Partially Observable Markov Decision Processes
231. ICML 2026TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
232. ICML 2026Tighter Regret Lower Bound for Gaussian Process Bandits with Squared Exponential Kernel in Hypersphere
233. ICML 2026Token Sample Complexity of Attention
234. ICML 2026Transformed Latent Variable Multi-Output Gaussian Processes
235. ICML 2026Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
236. NeurIPS 2026$R^3$: 3D Reconstruction via Relative Regression
237. NeurIPS 20263D Gaussian Splatting within Self-Learned Neural View-Dependent Color Fields
238. NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
239. NeurIPS 2026ACD-GS: Asymmetric Curvature-aware Densification for 3D Gaussian Splatting
240. NeurIPS 2026Active Learning for Gaussian Process Regression Under Self-Induced Boltzmann Weights
241. NeurIPS 2026Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
242. NeurIPS 2026Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models
243. NeurIPS 2026Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation
244. NeurIPS 2026Autoregressive Appearance Prediction for 3D Gaussian Avatars
245. NeurIPS 2026BEAST3D: animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
246. NeurIPS 2026Black-box model classification under the discriminative factorization
247. NeurIPS 2026Blur Issue Matters for Thermal Novel View Synthesis: A Floating Gaussian Suppression Approach
248. NeurIPS 2026Can Entry-Wise Clipping Give Spectral Control of Stochastic Gradients?
249. NeurIPS 2026CC-GS: Low-Memory 3D Gaussian Splatting Training via CPU-GPU Block-Wise Context Compositing
250. NeurIPS 2026CELEUS: Certifiable and Efficient LLM Evaluation via E-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.