处理效应论文趋势 2023–2026

ATE/CATE

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 385 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

处理效应论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023219331275
202432164018106
20253416311798
202644182717106

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

全部处理效应论文

共 40 篇,第 1 / 1 页

  1. ICML 2024A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
  2. ICML 2024Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice
  3. ICML 2024Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing
  4. ICML 2024Automating the Selection of Proxy Variables of Unmeasured Confounders
  5. ICML 2024Better Locally Private Sparse Estimation Given Multiple Samples Per User
  6. ICML 2024By Tying Embeddings You Are Assuming the Distributional Hypothesis
  7. ICML 2024Causal Effect Identification in LiNGAM Models with Latent Confounders
  8. ICML 2024Causal Inference out of Control: Estimating Performativity without Treatment Randomization
  9. ICML 2024Continuous Treatment Effects with Surrogate Outcomes
  10. ICML 2024Density Ratio Estimation with Doubly Strong Robustness
  11. ICML 2024DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
  12. ICML 2024DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
  13. ICML 2024Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
  14. ICML 2024Enabling Uncertainty Estimation in Iterative Neural Networks
  15. ICML 2024Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
  16. ICML 2024Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
  17. ICML 2024From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
  18. ICML 2024Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints
  19. ICML 2024Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
  20. ICML 2024Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
  21. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
  22. ICML 2024Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
  23. ICML 2024Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
  24. ICML 2024Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
  25. ICML 2024On Least Square Estimation in Softmax Gating Mixture of Experts
  26. ICML 2024Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
  27. ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
  28. ICML 2024Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
  29. ICML 2024Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
  30. ICML 2024Predicting Dose-Response Curves with Deep Neural Networks
  31. ICML 2024Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
  32. ICML 2024Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
  33. ICML 2024S$\Omega$I: Score-based O-INFORMATION Estimation
  34. ICML 2024Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
  35. ICML 2024Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
  36. ICML 2024Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
  37. ICML 2024Sub-token ViT Embedding via Stochastic Resonance Transformers
  38. ICML 2024The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
  39. ICML 2024Transitional Uncertainty with Layered Intermediate Predictions
  40. ICML 2024Uncertainty Estimation by Density Aware Evidential Deep Learning

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 查处理效应在 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": "treatment-effect"}

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处理效应论文?
共 385 篇,按年份分别是 2023 年 75 篇、2024 年 106 篇、2025 年 98 篇、2026 年 106 篇。
NeurIPS 2026 有多少篇处理效应论文?
NeurIPS 2026 有 44 篇处理效应论文,上一届是 34 篇。
ICLR 2026 有多少篇处理效应论文?
ICLR 2026 有 18 篇处理效应论文,上一届是 16 篇。
ICML 2026 有多少篇处理效应论文?
ICML 2026 有 27 篇处理效应论文,上一届是 31 篇。
CVPR 2026 有多少篇处理效应论文?
CVPR 2026 有 17 篇处理效应论文,上一届是 17 篇。
哪个会议的处理效应论文最多?
NeurIPS,2023–2026 年共 131 篇。

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