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 75 篇，第 2 / 2 页
- ICLR 2025When Selection Meets Intervention: Additional Complexities in Causal Discovery
- ICLR 2025Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression
- ICLR 2024A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
- ICLR 2024Can Large Language Models Infer Causation from Correlation?
- ICLR 2024Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning
- ICLR 2024Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
- ICLR 2024CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
- ICLR 2024CoLiDE: Concomitant Linear DAG Estimation
- ICLR 2024Federated Causal Discovery from Heterogeneous Data
- ICLR 2024Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
- ICLR 2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
- ICLR 2024Neural structure learning with stochastic differential equations
- ICLR 2024ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
- ICLR 2024Robust agents learn causal world models
- ICLR 2024Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
- ICLR 2023Boosting Causal Discovery via Adaptive Sample Reweighting
- ICLR 2023Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
- ICLR 2023Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems
- ICLR 2023CUTS: Neural Causal Discovery from Irregular Time-Series Data
- ICLR 2023DAG Learning on the Permutahedron
- ICLR 2023Diffusion Models for Causal Discovery via Topological Ordering
- ICLR 2023GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints
- ICLR 2023Improving the imputation of missing data with Markov Blanket discovery
- ICLR 2023Learning to Induce Causal Structure
- ICLR 2023Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise
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。