因果发现论文趋势 2023–2026
结构学习
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 379 篇被归入该主题的论文。
主要结论
- 因果发现论文从 2023 年的 59 篇增长到 2026 年的 139 篇，三年间扩大到约 2.4 倍。
- NeurIPS 是发因果发现论文最多的会议，2023–2026 年共 150 篇，占四个会议总量的 40%。
- 交叉方向里涨得最快的是通用机器学习 · unsupervised and semisupervised learning：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 10 篇。
- 在「因果与公平」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的偏见缓解是 1.5 倍，因果发现是 2.4 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 27 | 10 | 16 | 6 | 59 |
| 2024 | 36 | 13 | 32 | 1 | 82 |
| 2025 | 34 | 27 | 31 | 7 | 99 |
| 2026 | 53 | 25 | 54 | 7 | 139 |
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 Characterization of Latent Variable Causal Models Consistent with Observational Data
- ICML 2026A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables
- ICLR 2026Bures Generalized Category Discovery
- CVPR 2026Learning by Analogy A Causal Framework for Compositional Generalization
- NeurIPS 2025Causal Differentiating Concepts: Interpreting LM Behavior via Causal Representation Learning
- ICML 2025Bayesian Active Learning for Bivariate Causal Discovery
- ICLR 2025A Conditional Independence Test in the Presence of Discretization
- CVPR 2025Hyperbolic Category Discovery
- NeurIPS 2024Causal Bandits for Linear Structural Equation Models
- ICML 2024Adaptive Online Experimental Design for Causal Discovery
- ICLR 2024A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
- CVPR 2024Contrastive Mean-Shift Learning for Generalized Category Discovery
- NeurIPS 2023A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
- ICML 2023Active causal structure learning with advice
- ICLR 2023Boosting Causal Discovery via Adaptive Sample Reweighting
- CVPR 2023Intrinsic Physical Concepts Discovery With Object-Centric Predictive Models
- NeurIPS 2026Act, Validate, Adapt: Closing the Causal Discovery-Control Loop
- ICML 2026Causal Discovery for Irregularly Time Series with Consistency Guarantees
- ICLR 2026Causal Discovery in the Wild: A Voting-Theoretic Ensemble Approach
- CVPR 2026PlanaReLoc Camera Relocalization in 3D Planar Primitives via Region-Based Structure
全部因果发现论文
共 32 篇，第 1 / 1 页
- ICML 2024Adaptive Online Experimental Design for Causal Discovery
- ICML 2024Automated Statistical Model Discovery with Language Models
- ICML 2024Bivariate Causal Discovery using Bayesian Model Selection
- ICML 2024Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
- ICML 2024Causal Discovery via Conditional Independence Testing with Proxy Variables
- ICML 2024Causal Discovery with Fewer Conditional Independence Tests
- ICML 2024Causal Inference from Competing Treatments
- ICML 2024Causal Representation Learning Made Identifiable by Grouping of Observational Variables
- ICML 2024Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
- ICML 2024Collaborative Heterogeneous Causal Inference Beyond Meta-analysis
- ICML 2024Discovering Mixtures of Structural Causal Models from Time Series Data
- ICML 2024Enforcing Constraints in RNA Secondary Structure Predictions: A Post-Processing Framework Based on the Assignment Problem
- ICML 2024Foundations of Testing for Finite-Sample Causal Discovery
- ICML 2024How Transformers Learn Causal Structure with Gradient Descent
- ICML 2024Intersectional Unfairness Discovery
- ICML 2024Learning Causal Dynamics Models in Object-Oriented Environments
- ICML 2024Learning Causal Relations from Subsampled Time Series with Two Time-Slices
- ICML 2024Local Causal Structure Learning in the Presence of Latent Variables
- ICML 2024Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
- ICML 2024On Positivity Condition for Causal Inference
- ICML 2024On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data
- ICML 2024On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
- ICML 2024Optimal Kernel Choice for Score Function-based Causal Discovery
- ICML 2024Optimal Transport for Structure Learning Under Missing Data
- ICML 2024Reducing Balancing Error for Causal Inference via Optimal Transport
- ICML 2024Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
- ICML 2024Score-Based Causal Discovery of Latent Variable Causal Models
- ICML 2024Stable Differentiable Causal Discovery
- ICML 2024StableMask: Refining Causal Masking in Decoder-only Transformer
- ICML 2024Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders
- ICML 2024Transport of Algebraic Structure to Latent Embeddings
- ICML 2024Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
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 查因果发现在 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": "causal-discovery"}
常见问题
- 2023–2026 年四大会议一共有多少篇因果发现论文？
- 共 379 篇，按年份分别是 2023 年 59 篇、2024 年 82 篇、2025 年 99 篇、2026 年 139 篇。
- NeurIPS 2026 有多少篇因果发现论文？
- NeurIPS 2026 有 53 篇因果发现论文，上一届是 34 篇。
- ICLR 2026 有多少篇因果发现论文？
- ICLR 2026 有 25 篇因果发现论文，上一届是 27 篇。
- ICML 2026 有多少篇因果发现论文？
- ICML 2026 有 54 篇因果发现论文，上一届是 31 篇。
- CVPR 2026 有多少篇因果发现论文？
- CVPR 2026 有 7 篇因果发现论文，上一届是 7 篇。
- 哪个会议的因果发现论文最多？
- NeurIPS，2023–2026 年共 150 篇。