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 130 篇，第 1 / 3 页

1. CVPR 2023ECON: Explicit Clothed Humans Optimized via Normal Integration
2. ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
3. ICML 2023A/B Testing in Network Data with Covariate-Adaptive Randomization
4. ICML 2023Additive Causal Bandits with Unknown Graph
5. ICML 2023An Instrumental Variable Approach to Confounded Off-Policy Evaluation
6. ICML 2023Automatically marginalized MCMC in probabilistic programming
7. ICML 2023B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding
8. ICML 2023Causal Modeling of Policy Interventions From Treatment–Outcome Sequences
9. ICML 2023Constrained Causal Bayesian Optimization
10. ICML 2023Continual Task Allocation in Meta-Policy Network via Sparse Prompting
11. ICML 2023Correcting discount-factor mismatch in on-policy policy gradient methods
12. ICML 2023Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding
13. ICML 2023DRCFS: Doubly Robust Causal Feature Selection
14. ICML 2023Estimating Possible Causal Effects with Latent Variables via Adjustment
15. ICML 2023Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making
16. ICML 2023Fast Inference from Transformers via Speculative Decoding
17. ICML 2023Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space
18. ICML 2023Graph Inductive Biases in Transformers without Message Passing
19. ICML 2023In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
20. ICML 2023Inferring Relational Potentials in Interacting Systems
21. ICML 2023Instrumental Variable Estimation of Average Partial Causal Effects
22. ICML 2023Linear Causal Disentanglement via Interventions
23. ICML 2023Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
24. ICML 2023Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling
25. ICML 2023On Coresets for Clustering in Small Dimensional Euclidean spaces
26. ICML 2023Online Local Differential Private Quantile Inference via Self-normalization
27. ICML 2023Proximal Causal Learning of Conditional Average Treatment Effects
28. ICML 2023Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes
29. NeurIPS 2023$p$-Poisson surface reconstruction in curl-free flow from point clouds
30. NeurIPS 2023A Cross-Moment Approach for Causal Effect Estimation
31. NeurIPS 2023A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
32. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
33. NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
34. NeurIPS 2023Adversarial Counterfactual Environment Model Learning
35. NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
36. NeurIPS 2023Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
37. NeurIPS 2023Approximate inference of marginals using the IBIA framework
38. NeurIPS 2023Assumption violations in causal discovery and the robustness of score matching
39. NeurIPS 2023Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling
40. NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
41. NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
42. NeurIPS 2023Bounded rationality in structured density estimation
43. NeurIPS 2023C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
44. NeurIPS 2023CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
45. NeurIPS 2023Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments
46. NeurIPS 2023Causal Component Analysis
47. NeurIPS 2023Causal discovery from observational and interventional data across multiple environments
48. NeurIPS 2023Causal Discovery from Subsampled Time Series with Proxy Variables
49. NeurIPS 2023Causal Discovery in Semi-Stationary Time Series
50. NeurIPS 2023Causal Fairness for Outcome Control

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。