深度学习 · probabilistic methods论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：probabilistic_methods
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 637 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 69 | 7 | 25 | 6 | 107 |
| 2024 | 131 | 5 | 18 | 6 | 160 |
| 2025 | 212 | 10 | 37 | 4 | 263 |
| 2026 | 28 | 13 | 59 | 7 | 107 |
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 69 篇，第 2 / 2 页
- NeurIPS 2023Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks
- NeurIPS 2023Rehearsal Learning for Avoiding Undesired Future
- NeurIPS 2023SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning
- NeurIPS 2023SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation
- NeurIPS 2023Semi-Supervised Domain Generalization with Known and Unknown Classes
- NeurIPS 2023Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions
- NeurIPS 2023SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization
- NeurIPS 2023Smooth Flipping Probability for Differential Private Sign Random Projection Methods
- NeurIPS 2023Soft-Unification in Deep Probabilistic Logic
- NeurIPS 2023Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning
- NeurIPS 2023Star-Shaped Denoising Diffusion Probabilistic Models
- NeurIPS 2023Towards Accelerated Model Training via Bayesian Data Selection
- NeurIPS 2023Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars
- NeurIPS 2023Transformers learn to implement preconditioned gradient descent for in-context learning
- NeurIPS 2023Uncertainty Quantification via Neural Posterior Principal Components
- NeurIPS 2023Undirected Probabilistic Model for Tensor Decomposition
- NeurIPS 2023Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
- NeurIPS 2023VaRT: Variational Regression Trees
- NeurIPS 2023VeriX: Towards Verified Explainability of Deep Neural Networks
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查深度学习 · probabilistic methods在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "dl-probabilistic-methods"}
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。
「深度学习」下的其他主题
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · optimization 953
- 深度学习 · representation learning 802
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197