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. ICML 2023Adversarial robustness of amortized Bayesian inference
2. ICML 2023Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?
3. ICML 2023BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
4. ICML 2023Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates
5. ICML 2023Differentially Private Distributed Bayesian Linear Regression with MCMC
6. ICML 2023Distortion and Uncertainty Aware Loss for Panoramic Depth Completion
7. ICML 2023End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
8. ICML 2023Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes
9. ICML 2023Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
10. ICML 2023Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
11. ICML 2023MEWL: Few-shot multimodal word learning with referential uncertainty
12. ICML 2023On the Complexity of Bayesian Generalization
13. ICML 2023PAC-Bayesian Offline Contextual Bandits With Guarantees
14. ICML 2023PFNs4BO: In-Context Learning for Bayesian Optimization
15. ICML 2023Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs
16. ICML 2023Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds
17. ICML 2023Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances
18. ICML 2023spred: Solving L1 Penalty with SGD
19. ICML 2023Uncertainty Estimation by Fisher Information-based Evidential Deep Learning

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.