深度学习 · probabilistic methods论文趋势 2023–2026

主要结论

• 深度学习 · probabilistic methods论文从 2023 年的 107 篇增长到 2026 年的 107 篇，三年间扩大到约 1.0 倍。
• NeurIPS 是发深度学习 · probabilistic methods论文最多的会议，2023–2026 年共 440 篇，占四个会议总量的 69%。
• 交叉方向里涨得最快的是驾驶仿真：同时属于两个主题的论文从 2023 年的 5 篇增至 2026 年的 14 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 9；同组增长最快的扩散模型是 4.1 倍，深度学习 · probabilistic methods是 1.0 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部深度学习 · probabilistic methods论文

共 28 篇，第 1 / 1 页

1. NeurIPS 2026A Faster Algorithm for the Half-Trek Criterion in Structural Causal Models
2. NeurIPS 2026A probabilistic model of visual segmentation explains early visual cortical dynamics
3. NeurIPS 2026Affine Tracing: A New Paradigm for Probabilistic Linear Solvers
4. NeurIPS 2026Announced Breaks Separate Conformal Reliability from Frequency Calibration
5. NeurIPS 2026Auditing Conformal Prediction for Language Models Under Inference-Time Model Shift
6. NeurIPS 2026CoTs as Probabilistic Programs: A Programmatic View of Thinking Step-by-Step in Language Models
7. NeurIPS 2026Efficient Adaptive Data Acquisition via Pretrained Belief Representations
8. NeurIPS 2026Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
9. NeurIPS 2026Filtered-Trace Online Variational Training for Probabilistic Spiking Neural Networks
10. NeurIPS 2026FlowBatt: Flow Matching for Probabilistic Battery Degradation Prediction
11. NeurIPS 2026Heterogeneous Judge-Aware Ranking with Sensitivity, Disagreement, and Confidence
12. NeurIPS 2026Impossibility of Distribution-Free Predictive Inference for Individual Treatment Effects
13. NeurIPS 2026Inference and estimation with unidentifiable latent treatment effects
14. NeurIPS 2026Just Ramp-Up: Debiasing Regression-based Estimator for A/B Tests under Network Interference
15. NeurIPS 2026One-Shot Generative Flows: Existence and Obstructions
16. NeurIPS 2026Probabilistic Recursive Reasoning
17. NeurIPS 2026Probabilistic Signature Inversion: Learning Conditional Distributions from Truncated Signatures
18. NeurIPS 2026Probabilistic Tiny Recursive Model
19. NeurIPS 2026probly: Uncertainty-Aware Machine Learning
20. NeurIPS 2026Robust Conditional Conformal Prediction via Branched Normalizing Flow
21. NeurIPS 2026Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
22. NeurIPS 2026Score-based Variational Inference via Quantum Maximally Mixed States
23. NeurIPS 2026Sliced Inner Product Gromov–Wasserstein Distances
24. NeurIPS 2026Stabilizing Few-Shot Object Detection with Language-Conditioned Probabilistic Prototypes
25. NeurIPS 2026Stable GFlowNets with Probabilistic Guarantees
26. NeurIPS 2026The Expressivity Boundary of Probabilistic Circuits: A Comparison with Large Language Models
27. NeurIPS 2026Uncertainty-Aware Probabilistic Constrained Clustering from Entangled Pairwise Supervision
28. NeurIPS 2026Where to Approximate in Neurosymbolic Inference?

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · probabilistic methods论文？

共 637 篇，按年份分别是 2023 年 107 篇、2024 年 160 篇、2025 年 263 篇、2026 年 107 篇。

NeurIPS 2026 有多少篇深度学习 · probabilistic methods论文？

NeurIPS 2026 有 28 篇深度学习 · probabilistic methods论文，上一届是 212 篇。

ICLR 2026 有多少篇深度学习 · probabilistic methods论文？

ICLR 2026 有 13 篇深度学习 · probabilistic methods论文，上一届是 10 篇。

ICML 2026 有多少篇深度学习 · probabilistic methods论文？

ICML 2026 有 59 篇深度学习 · probabilistic methods论文，上一届是 37 篇。

CVPR 2026 有多少篇深度学习 · probabilistic methods论文？

CVPR 2026 有 7 篇深度学习 · probabilistic methods论文，上一届是 4 篇。

哪个会议的深度学习 · probabilistic methods论文最多？

NeurIPS，2023–2026 年共 440 篇。