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 36 篇,第 1 / 1 页
- NeurIPS 2024A Simple yet Scalable Granger Causal Structural Learning Approach for Topological Event Sequences
- NeurIPS 2024Amortized Active Causal Induction with Deep Reinforcement Learning
- NeurIPS 2024Causal Bandits for Linear Structural Equation Models
- NeurIPS 2024Causal Discovery from Event Sequences by Local Cause-Effect Attribution
- NeurIPS 2024Causal discovery with endogenous context variables
- NeurIPS 2024Causal vs. Anticausal merging of predictors
- NeurIPS 2024Causal-learn: Causal Discovery in Python
- NeurIPS 2024CausalStock: Deep End-to-end Causal Discovery for News-driven Multi-stock Movement Prediction
- NeurIPS 2024ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions
- NeurIPS 2024Clustering in Causal Attention Masking
- NeurIPS 2024Differentiable Structure Learning with Partial Orders
- NeurIPS 2024Discovery of the Hidden World with Large Language Models
- NeurIPS 2024Do causal predictors generalize better to new domains?
- NeurIPS 2024Do Finetti: On Causal Effects for Exchangeable Data
- NeurIPS 2024Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention
- NeurIPS 2024Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
- NeurIPS 2024Identifying Causal Effects Under Functional Dependencies
- NeurIPS 2024Interventional Causal Discovery in a Mixture of DAGs
- NeurIPS 2024Learning Discrete Concepts in Latent Hierarchical Models
- NeurIPS 2024Learning Discrete Latent Variable Structures with Tensor Rank Conditions
- NeurIPS 2024Learning Identifiable Factorized Causal Representations of Cellular Responses
- NeurIPS 2024Learning Mixtures of Unknown Causal Interventions
- NeurIPS 2024Learning the Latent Causal Structure for Modeling Label Noise
- NeurIPS 2024MECD: Unlocking Multi-Event Causal Discovery in Video Reasoning
- NeurIPS 2024On Causal Discovery in the Presence of Deterministic Relations
- NeurIPS 2024On the Complexity of Identification in Linear Structural Causal Models
- NeurIPS 2024On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
- NeurIPS 2024On the Parameter Identifiability of Partially Observed Linear Causal Models
- NeurIPS 2024Optimal ablation for interpretability
- NeurIPS 2024Ordering-Based Causal Discovery for Linear and Nonlinear Relations
- NeurIPS 2024Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
- NeurIPS 2024QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
- NeurIPS 2024Sample Complexity of Interventional Causal Representation Learning
- NeurIPS 2024Sample Efficient Bayesian Learning of Causal Graphs from Interventions
- NeurIPS 2024Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems
- 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"}
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。