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

每年论文数

各会议论文数

按年份和会议统计

因果发现论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023271016659
2024361332182
2025342731799
20265325547139

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

全部因果发现论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 82 篇，第 2 / 2 页

  1. NeurIPS 2024Causal discovery with endogenous context variables
  2. NeurIPS 2024Causal vs. Anticausal merging of predictors
  3. NeurIPS 2024Causal-learn: Causal Discovery in Python
  4. NeurIPS 2024CausalStock: Deep End-to-end Causal Discovery for News-driven Multi-stock Movement Prediction
  5. NeurIPS 2024ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions
  6. NeurIPS 2024Clustering in Causal Attention Masking
  7. NeurIPS 2024Differentiable Structure Learning with Partial Orders
  8. NeurIPS 2024Discovery of the Hidden World with Large Language Models
  9. NeurIPS 2024Do causal predictors generalize better to new domains?
  10. NeurIPS 2024Do Finetti: On Causal Effects for Exchangeable Data
  11. NeurIPS 2024Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention
  12. NeurIPS 2024Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
  13. NeurIPS 2024Identifying Causal Effects Under Functional Dependencies
  14. NeurIPS 2024Interventional Causal Discovery in a Mixture of DAGs
  15. NeurIPS 2024Learning Discrete Concepts in Latent Hierarchical Models
  16. NeurIPS 2024Learning Discrete Latent Variable Structures with Tensor Rank Conditions
  17. NeurIPS 2024Learning Identifiable Factorized Causal Representations of Cellular Responses
  18. NeurIPS 2024Learning Mixtures of Unknown Causal Interventions
  19. NeurIPS 2024Learning the Latent Causal Structure for Modeling Label Noise
  20. NeurIPS 2024MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning
  21. NeurIPS 2024On Causal Discovery in the Presence of Deterministic Relations
  22. NeurIPS 2024On the Complexity of Identification in Linear Structural Causal Models
  23. NeurIPS 2024On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
  24. NeurIPS 2024On the Parameter Identifiability of Partially Observed Linear Causal Models
  25. NeurIPS 2024Optimal ablation for interpretability
  26. NeurIPS 2024Ordering-Based Causal Discovery for Linear and Nonlinear Relations
  27. NeurIPS 2024Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
  28. NeurIPS 2024QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
  29. NeurIPS 2024Sample Complexity of Interventional Causal Representation Learning
  30. NeurIPS 2024Sample Efficient Bayesian Learning of Causal Graphs from Interventions
  31. NeurIPS 2024Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems
  32. NeurIPS 2024WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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