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

24 papers, page 1 of 1

1. ICML 2025BARNN: A Bayesian Autoregressive and Recurrent Neural Network
2. ICML 2025Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
3. ICML 2025Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
4. ICML 2025BILBO: BILevel Bayesian Optimization
5. ICML 2025Can Transformers Learn Full Bayesian Inference in Context?
6. ICML 2025Conformal Prediction as Bayesian Quadrature
7. ICML 2025Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
8. ICML 2025Deep Bayesian Filter for Bayes-Faithful Data Assimilation
9. ICML 2025Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
10. ICML 2025FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
11. ICML 2025GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
12. ICML 2025Harnessing Heterogeneous Statistical Strength for Personalized Federated Learning via Hierarchical Bayesian Inference
13. ICML 2025Improving Generalization with Flat Hilbert Bayesian Inference
14. ICML 2025Latent Variable Estimation in Bayesian Black-Litterman Models
15. ICML 2025LEAPS: A discrete neural sampler via locally equivariant networks
16. ICML 2025Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response
17. ICML 2025Learning Gaussian DAG Models without Condition Number Bounds
18. ICML 2025Linearization Turns Neural Operators into Function-Valued Gaussian Processes
19. ICML 2025Maximizing Intermediate Checkpoint Value in LLM Pretraining with Bayesian Optimization
20. ICML 2025Models of Heavy-Tailed Mechanistic Universality
21. ICML 2025Position: The Future of Bayesian Prediction Is Prior-Fitted
22. ICML 2025Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
23. ICML 2025Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
24. ICML 2025Scalable Gaussian Processes with Latent Kronecker Structure

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.