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 3 of 8

101. NeurIPS 2026U-MVP: Encode Locally, Decode Globally for Feed-Forward 3D Gaussian Splatting
102. NeurIPS 2026UltraVoxelGS: Voxel-First Feed-Forward Gaussian Splatting for 3D Ultrasound Reconstruction
103. NeurIPS 2026Umbilic Multinomial Logistic Regression
104. NeurIPS 2026UniGS: Unified Geometry-Aware Gaussian Splatting for Multimodal Rendering
105. NeurIPS 2026Very Fast Bayesian Additive Regression Trees on GPU
106. NeurIPS 2026When does LeJEPA learn a World Model?
107. NeurIPS 2025$\text{G}^2\text{M}$: A Generalized Gaussian Mirror Method to Boost Feature Selection Power
108. NeurIPS 20251000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering
109. NeurIPS 20253D Gaussian Flats: Hybrid 2D/3D Photometric Scene Reconstruction
110. NeurIPS 20253D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes
111. NeurIPS 20254DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos
112. NeurIPS 2025A Provable Approach for End-to-End Safe Reinforcement Learning
113. NeurIPS 2025Abstract Rendering: Certified Rendering Under 3D Semantic Uncertainty
114. NeurIPS 2025Accelerated Evolving Set Processes for Local PageRank Computation
115. NeurIPS 2025Achieving $\tilde{\mathcal{O}}(1/N)$ Optimality Gap in Restless Bandits through Gaussian Approximation
116. NeurIPS 2025Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
117. NeurIPS 2025Addressing Mark Imbalance in Integration-free Marked Temporal Point Processes
118. NeurIPS 2025Anti-Aliased 2D Gaussian Splatting
119. NeurIPS 2025Approximation and Generalization Abilities of Score-based Neural Network Generative Models for Sub-Gaussian Distributions
120. NeurIPS 2025Assessing the quality of denoising diffusion models in Wasserstein distance: noisy score and optimal bounds
121. NeurIPS 2025AtlasGS: Atlanta-world Guided Surface Reconstruction with Implicit Structured Gaussians
122. NeurIPS 2025Autoregressive Motion Generation with Gaussian Mixture-Guided Latent Sampling
123. NeurIPS 2025BecomingLit: Relightable Gaussian Avatars with Hybrid Neural Shading
124. NeurIPS 2025BevSplat: Resolving Height Ambiguity via Feature-Based Gaussian Primitives for Weakly-Supervised Cross-View Localization
125. NeurIPS 2025Bivariate Matrix-valued Linear Regression (BMLR): Finite-sample performance under Identifiability and Sparsity Assumptions
126. NeurIPS 2025CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis
127. NeurIPS 2025Deep Gaussian from Motion: Exploring 3D Geometric Foundation Models for Gaussian Splatting
128. NeurIPS 2025DEGauss: Defending Against Malicious 3D Editing for Gaussian Splatting
129. NeurIPS 2025DGH: Dynamic Gaussian Hair
130. NeurIPS 2025Distance-informed Neural Processes
131. NeurIPS 2025DrivingRecon: Large 4D Gaussian Reconstruction Model For Autonomous Driving
132. NeurIPS 2025Dynamic Gaussian Splatting from Defocused and Motion-blurred Monocular Videos
133. NeurIPS 2025EF-3DGS: Event-Aided Free-Trajectory 3D Gaussian Splatting
134. NeurIPS 2025Efficient Training of Minimal and Maximal Low-Rank Recurrent Neural Networks
135. NeurIPS 2025EGGS: Exchangeable 2D/3D Gaussian Splatting for Geometry-Appearance Balanced Novel View Synthesis
136. NeurIPS 2025Faster Fixed-Point Methods for Multichain MDPs
137. NeurIPS 2025FHGS: Feature-Homogenized Gaussian Splatting
138. NeurIPS 2025Flow Matching Neural Processes
139. NeurIPS 2025Gaussian Approximation and Concentration of Constant Learning-Rate Stochastic Gradient Descent
140. NeurIPS 2025Gaussian Herding across Pens: An Optimal Transport Perspective on Global Gaussian Reduction for 3DGS
141. NeurIPS 2025Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
142. NeurIPS 2025Gaussian Processes for Shuffled Regression
143. NeurIPS 2025Gaussian Regression-Driven Tensorized Incomplete Multi-View Clustering with Dual Manifold Regularization
144. NeurIPS 2025Go With the Flow: Fast Diffusion for Gaussian Mixture Models
145. NeurIPS 2025GSRF: Complex-Valued 3D Gaussian Splatting for Efficient Radio-Frequency Data Synthesis
146. NeurIPS 2025H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting
147. NeurIPS 2025HAIF-GS: Hierarchical and Induced Flow-Guided Gaussian Splatting for Dynamic Scene
148. NeurIPS 2025HoliGS: Holistic Gaussian Splatting for Embodied View Synthesis
149. NeurIPS 2025Holistic Large-Scale Scene Reconstruction via Mixed Gaussian Splatting
150. NeurIPS 2025How Data Mixing Shapes In-Context Learning: Asymptotic Equivalence for Transformers with MLPs

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.