经济因果论文趋势 2023–2026

主要结论

• 经济因果论文从 2023 年的 130 篇降到 2026 年的 27 篇，热度在回落。
• NeurIPS 是发经济因果论文最多的会议，2023–2026 年共 117 篇，占四个会议总量的 64%。
• 交叉方向里涨得最快的是强化学习：同时属于两个主题的论文从 2023 年的 12 篇增至 2026 年的 10 篇。
• 在「金融与经济」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的宏观预测是 8.0 倍，经济因果是 0.2 倍。

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 2026Characterizing Underrepresentation in Generalizing Causal Survival Estimates
• ICML 2026Independent Component Discovery in Temporal Count Data
• ICLR 2026Ice Cream Doesn’t Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference
• CVPR 2026COPO Causal-Oriented Policy Optimization for Hallucinations of MLLMs
• NeurIPS 2025Causal Explanation-Guided Learning for Organ Allocation
• ICML 2025Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
• ICLR 2025Incremental Causal Effect for Time to Treatment Initialization
• NeurIPS 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
• ICML 2024Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness
• ICLR 2024Learning in reverse causal strategic environments with ramifications on two sided markets
• NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
• ICML 2023B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding
• ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
• CVPR 2023ECON: Explicit Clothed Humans Optimized via Normal Integration
• NeurIPS 2026Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
• ICML 2026Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settings
• ICLR 2026Foundation Models for Causal Inference via Prior-Data Fitted Networks
• NeurIPS 2025Pessimistic Data Integration for Policy Evaluation
• ICML 2025Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
• ICLR 2025Efficient Causal Decision Making with One-sided Feedback

全部经济因果论文

共 102 篇，第 1 / 3 页

1. NeurIPS 2023$p$-Poisson surface reconstruction in curl-free flow from point clouds
2. NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
3. NeurIPS 2023A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
4. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
5. NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
6. NeurIPS 2023Adversarial Counterfactual Environment Model Learning
7. NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
8. NeurIPS 2023Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
9. NeurIPS 2023Approximate inference of marginals using the IBIA framework
10. NeurIPS 2023Assumption violations in causal discovery and the robustness of score matching
11. NeurIPS 2023Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling
12. NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
13. NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
14. NeurIPS 2023Bounded rationality in structured density estimation
15. NeurIPS 2023C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
16. NeurIPS 2023CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
17. NeurIPS 2023Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments
18. NeurIPS 2023Causal Component Analysis
19. NeurIPS 2023Causal discovery from observational and interventional data across multiple environments
20. NeurIPS 2023Causal Discovery from Subsampled Time Series with Proxy Variables
21. NeurIPS 2023Causal Discovery in Semi-Stationary Time Series
22. NeurIPS 2023Causal Fairness for Outcome Control
23. NeurIPS 2023Causal Imitability Under Context-Specific Independence Relations
24. NeurIPS 2023Causal Interpretation of Self-Attention in Pre-Trained Transformers
25. NeurIPS 2023Causal normalizing flows: from theory to practice
26. NeurIPS 2023Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing
27. NeurIPS 2023Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
28. NeurIPS 2023Change point detection and inference in multivariate non-parametric models under mixing conditions
29. NeurIPS 2023CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
30. NeurIPS 2023Common Ground in Cooperative Communication
31. NeurIPS 2023Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
32. NeurIPS 2023Conformalized matrix completion
33. NeurIPS 2023Convex-Concave Zero-Sum Markov Stackelberg Games
34. NeurIPS 2023Counterfactual Evaluation of Peer-Review Assignment Policies
35. NeurIPS 2023Counterfactually Comparing Abstaining Classifiers
36. NeurIPS 2023CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews
37. NeurIPS 2023Demystifying Softmax Gating Function in Gaussian Mixture of Experts
38. NeurIPS 2023Detecting hidden confounding in observational data using multiple environments
39. NeurIPS 2023Differentially Private Approximate Near Neighbor Counting in High Dimensions
40. NeurIPS 2023Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data
41. NeurIPS 2023Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
42. NeurIPS 2023Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams
43. NeurIPS 2023Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
44. NeurIPS 2023Fair Adaptive Experiments
45. NeurIPS 2023Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
46. NeurIPS 2023Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time
47. NeurIPS 2023Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
48. NeurIPS 2023Gaussian Membership Inference Privacy
49. NeurIPS 2023GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
50. NeurIPS 2023Hierarchical VAEs provide a normative account of motion processing in the primate brain

常见问题

2023–2026 年四大会议一共有多少篇经济因果论文？

共 183 篇，按年份分别是 2023 年 130 篇、2024 年 10 篇、2025 年 16 篇、2026 年 27 篇。

NeurIPS 2026 有多少篇经济因果论文？

NeurIPS 2026 有 4 篇经济因果论文，上一届是 6 篇。

ICLR 2026 有多少篇经济因果论文？

ICLR 2026 有 5 篇经济因果论文，上一届是 4 篇。

ICML 2026 有多少篇经济因果论文？

ICML 2026 有 17 篇经济因果论文，上一届是 6 篇。

CVPR 2026 有多少篇经济因果论文？

CVPR 2026 有 1 篇经济因果论文。

哪个会议的经济因果论文最多？

NeurIPS，2023–2026 年共 117 篇。