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

19 papers, page 1 of 1

1. ICLR 2023Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference
2. ICLR 2023Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation
3. ICLR 2023Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle
4. ICLR 2023Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
5. ICLR 2023Batch Multivalid Conformal Prediction
6. ICLR 2023BSTT: A Bayesian Spatial-Temporal Transformer for Sleep Staging
7. ICLR 2023Calibrating Transformers via Sparse Gaussian Processes
8. ICLR 2023Deep Variational Implicit Processes
9. ICLR 2023Latent Neural ODEs with Sparse Bayesian Multiple Shooting
10. ICLR 2023Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
11. ICLR 2023MARS: Meta-learning as Score Matching in the Function Space
12. ICLR 2023Martingale Posterior Neural Processes
13. ICLR 2023Model-based Causal Bayesian Optimization
14. ICLR 2023Robustness to corruption in pre-trained Bayesian neural networks
15. ICLR 2023SAM as an Optimal Relaxation of Bayes
16. ICLR 2023Sampling-based inference for large linear models, with application to linearised Laplace
17. ICLR 2023Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
18. ICLR 2023Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
19. ICLR 2023Transfer NAS with Meta-learned Bayesian Surrogates

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.