Bayesian Deep Learning papers, 2023–2026

Key findings

• Bayesian Deep Learning went from 112 papers in 2023 to 112 in 2026, roughly 1.0x in three years.
• NeurIPS publishes the most Bayesian Deep Learning work: 165 papers from 2023 to 2026, 40% of the four-venue total.
• The fastest-growing overlap is with Simulation for Driving: papers tagged with both rose from 5 in 2023 to 11 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #4 by 2026 paper count; the fastest grower in the group, Gaussian Processes, is up 2.2x versus 1.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Approximate Bayesian inference with exchangeable distributions for neurosymbolic AI
• ICML 2026A Bayesian Approach to Quantify the Uncertainty of Human Ratings in a Single-Instance Multimodal Framework
• ICLR 2026Bayesian Neural Networks for Functional ANOVA Model
• CVPR 2026CGU-Bayes Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization
• NeurIPS 2025A Bayesian Approach to Contextual Dynamic Pricing using the Proportional Hazards Model with Discrete Price Data
• ICML 2025BARNN: A Bayesian Autoregressive and Recurrent Neural Network
• ICLR 2025Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior
• CVPR 2025HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
• NeurIPS 2024Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems
• ICML 2024Bayesian Knowledge Distillation: A Bayesian Perspective of Distillation with Uncertainty Quantification
• ICLR 2024A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
• CVPR 2024Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
• NeurIPS 2023A Bayesian Approach To Analysing Training Data Attribution In Deep Learning
• ICML 2023Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?
• ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
• CVPR 2023Bayesian Posterior Approximation With Stochastic Ensembles
• NeurIPS 2026BO-Arena: An Evolving Benchmark for High-Dimensional Bayesian Optimisation
• ICML 2026Bayesian Gated Non-Negative Contrastive Learning
• ICLR 2026Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
• CVPR 2026Evidential Deep Partial Label Learning to Quantify Disambiguation Uncertainty

All Bayesian Deep Learning papers

25 papers, page 1 of 1

1. CVPR 2026AdaPrior Bayesian-Inspired Adaptive Prior Correction for Long-Tailed Continual Learning
2. CVPR 2026Adapting Point Cloud Analysis via Multimodal Bayesian Distribution Learning
3. CVPR 2026CGU-Bayes Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization
4. CVPR 2026Defending Unauthorized Model Merging via Dual-Stage Weight Protection
5. CVPR 2026Enhancing Accuracy of Uncertainty Estimation in Appearance-based Gaze Tracking with
6. CVPR 2026Evidential Deep Partial Label Learning to Quantify Disambiguation Uncertainty
7. CVPR 2026PhysGS Bayesian-Inferred Gaussian Splatting for Physical Property Estimation
8. CVPR 2026ReBaPL Repulsive Bayesian Prompt Learning
9. CVPR 2026Spectral Conformal Risk Control Distribution-Free Tail Guarantees via Bayesian Quadrature
10. CVPR 2025HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
11. CVPR 2025Investigating the Role of Weight Decay in Enhancing Nonconvex SGD
12. CVPR 2025LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty
13. CVPR 2024Bayes' Rays: Uncertainty Quantification for Neural Radiance Fields
14. CVPR 2024Bayesian Differentiable Physics for Cloth Digitalization
15. CVPR 2024Bayesian Diffusion Models for 3D Shape Reconstruction
16. CVPR 2024Epistemic Uncertainty Quantification For Pre-Trained Neural Networks
17. CVPR 2024Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
18. CVPR 2024Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
19. CVPR 2024Uncertainty Visualization via Low-Dimensional Posterior Projections
20. CVPR 2023Bayesian Posterior Approximation With Stochastic Ensembles
21. CVPR 2023Deep Deterministic Uncertainty: A New Simple Baseline
22. CVPR 2023Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning
23. CVPR 2023Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization
24. CVPR 2023Spectral Bayesian Uncertainty for Image Super-Resolution
25. CVPR 2023Training Debiased Subnetworks With Contrastive Weight Pruning

FAQ

How many Bayesian Deep Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

408 in total: 112 in 2023, 100 in 2024, 84 in 2025, 112 in 2026.

How many Bayesian Deep Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 40 Bayesian Deep Learning papers, versus 27 the year before.

How many Bayesian Deep Learning papers are at ICLR 2026?

ICLR 2026 has 22 Bayesian Deep Learning papers, versus 30 the year before.

How many Bayesian Deep Learning papers are at ICML 2026?

ICML 2026 has 41 Bayesian Deep Learning papers, versus 24 the year before.

How many Bayesian Deep Learning papers are at CVPR 2026?

CVPR 2026 has 9 Bayesian Deep Learning papers, versus 3 the year before.

Which conference publishes the most Bayesian Deep Learning papers?

NeurIPS, with 165 papers from 2023 to 2026.