Deep learning · probabilistic methods papers, 2023–2026

Key findings

• Deep learning · probabilistic methods went from 107 papers in 2023 to 107 in 2026, roughly 1.0x in three years.
• NeurIPS publishes the most Deep learning · probabilistic methods work: 440 papers from 2023 to 2026, 69% of the four-venue total.
• The fastest-growing overlap is with Simulation for Driving: papers tagged with both rose from 5 in 2023 to 14 in 2026.
• Among the 11 topics under Deep Learning, it ranks #9 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 1.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Faster Algorithm for the Half-Trek Criterion in Structural Causal Models
• ICML 2026An Efficient Joint Learning Approach for Item Response Theory
• ICLR 2026Probabilistic Kernel Function for Fast Angle Testing
• CVPR 2026Beyond Text Visual Description Assembly by Probabilistic Model for CLIP-based
• NeurIPS 2025$\text{G}^2\text{M}$: A Generalized Gaussian Mirror Method to Boost Feature Selection Power
• ICML 2025Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
• ICLR 2025P-SPIKESSM: HARNESSING PROBABILISTIC SPIKING STATE SPACE MODELS FOR LONG-RANGE DEPENDENCY TASKS
• CVPR 2025ProbPose: A Probabilistic Approach to 2D Human Pose Estimation
• NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
• ICML 2024A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs
• ICLR 2024A Probabilistic Framework for Modular Continual Learning
• CVPR 2024CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
• NeurIPS 2023A Computationally Efficient Sparsified Online Newton Method
• ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
• ICLR 2023A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation
• CVPR 2023Probabilistic Knowledge Distillation of Face Ensembles
• NeurIPS 2026Affine Tracing: A New Paradigm for Probabilistic Linear Solvers
• ICML 2026Avoid What You Know: Divergent Trajectory Balance for GFlowNets
• ICLR 2026Learning Survival Distributions with Individually Calibrated Asymmetric Laplace Distribution
• CVPR 2026ARES Unifying Asymmetric RGB-Event Stereo for Probabilistic Scene Flow Estimation

All Deep learning · probabilistic methods papers

23 papers, page 1 of 1

1. CVPR 2026ARES Unifying Asymmetric RGB-Event Stereo for Probabilistic Scene Flow Estimation
2. CVPR 2026Beyond Text Visual Description Assembly by Probabilistic Model for CLIP-based
3. CVPR 2026Elucidating the SNR-t Bias of Diffusion Probabilistic Models
4. CVPR 2026JoPPO Hierarchical Photography Assessment via Contrastive Joint Conditional Probabilistic Reinforcement
5. CVPR 2026Probabilistic Discrepancy Learning for Roadside LiDAR Scene Completion
6. CVPR 2026Probabilistic Precipitation Nowcasting with Rectified Flow Transformers
7. CVPR 2026ProM3E Probabilistic Masked MultiModal Embedding Model for Ecology
8. CVPR 2025Fingerprinting Denoising Diffusion Probabilistic Models
9. CVPR 2025Probabilistic Prompt Distribution Learning for Animal Pose Estimation
10. CVPR 2025ProbPose: A Probabilistic Approach to 2D Human Pose Estimation
11. CVPR 2025SyncSDE: A Probabilistic Framework for Diffusion Synchronization
12. CVPR 2024A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling
13. CVPR 2024CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
14. CVPR 2024DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans
15. CVPR 2024Observation-Guided Diffusion Probabilistic Models
16. CVPR 2024Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computing
17. CVPR 2024ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring
18. CVPR 2023Diffusion Probabilistic Model Made Slim
19. CVPR 2023Lookahead Diffusion Probabilistic Models for Refining Mean Estimation
20. CVPR 2023Probabilistic Debiasing of Scene Graphs
21. CVPR 2023Probabilistic Knowledge Distillation of Face Ensembles
22. CVPR 2023Probabilistic Prompt Learning for Dense Prediction
23. CVPR 2023Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration

FAQ

How many Deep learning · probabilistic methods papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

637 in total: 107 in 2023, 160 in 2024, 263 in 2025, 107 in 2026.

How many Deep learning · probabilistic methods papers are at NeurIPS 2026?

NeurIPS 2026 has 28 Deep learning · probabilistic methods papers, versus 212 the year before.

How many Deep learning · probabilistic methods papers are at ICLR 2026?

ICLR 2026 has 13 Deep learning · probabilistic methods papers, versus 10 the year before.

How many Deep learning · probabilistic methods papers are at ICML 2026?

ICML 2026 has 59 Deep learning · probabilistic methods papers, versus 37 the year before.

How many Deep learning · probabilistic methods papers are at CVPR 2026?

CVPR 2026 has 7 Deep learning · probabilistic methods papers, versus 4 the year before.

Which conference publishes the most Deep learning · probabilistic methods papers?

NeurIPS, with 440 papers from 2023 to 2026.