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
- 处理效应论文从 2023 年的 75 篇增长到 2026 年的 106 篇,三年间扩大到约 1.4 倍。
- NeurIPS 是发处理效应论文最多的会议,2023–2026 年共 131 篇,占四个会议总量的 34%。
- 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 2;同组增长最快的因果发现是 2.4 倍,处理效应是 1.4 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 21 | 9 | 33 | 12 | 75 |
| 2024 | 32 | 16 | 40 | 18 | 106 |
| 2025 | 34 | 16 | 31 | 17 | 98 |
| 2026 | 44 | 18 | 27 | 17 | 106 |
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 2026Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
- ICML 2026Causal Effect Identifiability in the Presence of Latent Confounders Without Auxiliary Variables
- ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
- CVPR 2026Event Stream Filtering via Probability Flux Estimation
- NeurIPS 2025Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities
- ICML 2025A Meta-learner for Heterogeneous Effects in Difference-in-Differences
- ICLR 2025Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables
- CVPR 2025Any6D: Model-free 6D Pose Estimation of Novel Objects
- NeurIPS 2024Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
- ICML 2024A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
- ICLR 2024A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
- CVPR 2024LightOctree: Lightweight 3D Spatially-Coherent Indoor Lighting Estimation
- NeurIPS 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effect
- ICML 2023A Three-regime Model of Network Pruning
- ICLR 2023Causal Estimation for Text Data with (Apparent) Overlap Violations
- CVPR 2023HRDFuse: Monocular 360deg Depth Estimation by Collaboratively Learning Holistic-With-Regional Depth Distributions
- NeurIPS 2026Automated Causal Effect Estimation through Self-Evolving AI
- ICML 2026Causal-EPIG: Causally Aligned Active CATE Estimation
- ICLR 2026Foundation Models for Causal Inference via Prior-Data Fitted Networks
- CVPR 2026The Invisible Gorilla Effect in Out-of-distribution Detection
全部处理效应论文
共 131 篇,第 1 / 3 页
- NeurIPS 2026Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring
- NeurIPS 2026Automated Causal Effect Estimation through Self-Evolving AI
- NeurIPS 2026Bayesian Causal Experimental Design for CATE Estimation under Noncompliance
- NeurIPS 2026Bayesian Causal Stress Testing: Posterior Fragility of Treatment-Effect Conclusions
- NeurIPS 2026Causal Effect Identification with a Single Agnostic Proxy
- NeurIPS 2026Conditional Counterfactual Mean Embeddings: Doubly Robust Estimation and Learning Rates
- NeurIPS 2026Conservative Continuous-Time Treatment Optimization
- NeurIPS 2026Conservative neural posterior estimation via distributionally robust training
- NeurIPS 2026CUVET: A Partitioning Approach for Continuous Treatment Assignment At Scale
- NeurIPS 2026DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
- NeurIPS 2026Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
- NeurIPS 2026Decision-Aware Proximal Bridge Learning for Optimal Treatment Selection
- NeurIPS 2026Distribution-First Framework for Learning Risk-Sensitive Individualized Treatment Rules
- NeurIPS 2026Distributional Estimation of 3D Object Orientation
- NeurIPS 2026Dynamic Treatment on Networks
- NeurIPS 2026Effect-Level Validation for Causal Discovery in Interactive Telemetry
- NeurIPS 2026Explainability matters: The effect of liability rules on the healthcare sector
- NeurIPS 2026Fair Division of Work in Collaborative Mean Estimation via Bargaining
- NeurIPS 2026FMMI: Flow Matching Mutual Information Estimation
- NeurIPS 2026Focusable Monocular Depth Estimation
- NeurIPS 2026Free energy Estimation on Any State Space
- NeurIPS 2026From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features
- NeurIPS 2026Global Importance Estimation for KV Cache Eviction
- NeurIPS 2026Impossibility of Distribution-Free Predictive Inference for Individual Treatment Effects
- NeurIPS 2026Inference and estimation with unidentifiable latent treatment effects
- NeurIPS 2026Integrating digital twins with randomized experiments
- NeurIPS 2026Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
- NeurIPS 2026Learning Modular Addition with Auxiliary Modulus
- NeurIPS 2026Metric Depth Estimation from Arbitrarily Degraded Low-Resolution Depth Prompts
- NeurIPS 2026Mitigating Data Heterogeneity Effect in Client-Reshuffling-Based Federated Learning
- NeurIPS 2026MSConsensus: A Hundred-Million-Scale, Batch-Effect–Suppressed Dataset and Benchmark for Proteomics Machine Learning
- NeurIPS 2026Negation Neglect: When models fail to learn negations in training
- NeurIPS 2026On the Effect of Token Correlations on Semantic Transfer in Transformers
- NeurIPS 2026Phase Transitions in Heavy-Tailed Mean Estimation under $\ell_p$ Norms
- NeurIPS 2026Provably Accurate Shapley Value Estimation in High Dimensions via Sparse Leverage Sampling
- NeurIPS 2026Roll2Depth: Zero-Shot Metric Depth Estimation Exploiting Camera's Rolling Shutter Effect
- NeurIPS 2026Settling Pure Differentially Private Covariance Estimation
- NeurIPS 2026Spectral Estimation with Deformed Decompression
- NeurIPS 2026The Butterfly Effect in Reasoning: Branch-Structured Distributional Memory for Stochastic Agents
- NeurIPS 2026The Deadline Effect: Identifying and Correcting Temporal Bias in Human Evaluation
- NeurIPS 2026The Heavy Hitter Oracle: Enhancing Frequency Estimation in Skewed Data Streams
- NeurIPS 2026Total Variation Distance Estimation in Autoregressive Models
- NeurIPS 2026Unified High-Probability Analysis of Stochastic Variance-Reduced Estimation
- NeurIPS 2026What the Geometry of Good Models Tells Us
- NeurIPS 2025Adaptive Data-Borrowing for Improving Treatment Effect Estimation using External Controls
- NeurIPS 2025An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation
- NeurIPS 2025Beyond the Average: Distributional Causal Inference under Imperfect Compliance
- NeurIPS 2025Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities
- NeurIPS 2025CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
- NeurIPS 2025CMoB: Modality Valuation via Causal Effect for Balanced Multimodal 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"}
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。