Treatment Effect papers, 2023–2026

Key findings

• Treatment Effect went from 75 papers in 2023 to 106 in 2026, roughly 1.4x in three years.
• NeurIPS publishes the most Treatment Effect work: 131 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with General ML · unsupervised and semisupervised learning: papers tagged with both rose from 3 in 2023 to 10 in 2026.
• Among the 5 topics under Causal and Fairness, it ranks #2 by 2026 paper count; the fastest grower in the group, Causal Discovery, is up 2.4x versus 1.4x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Treatment Effect papers

40 papers, page 1 of 1

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

FAQ

How many Treatment Effect papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

385 in total: 75 in 2023, 106 in 2024, 98 in 2025, 106 in 2026.

How many Treatment Effect papers are at NeurIPS 2026?

NeurIPS 2026 has 44 Treatment Effect papers, versus 34 the year before.

How many Treatment Effect papers are at ICLR 2026?

ICLR 2026 has 18 Treatment Effect papers, versus 16 the year before.

How many Treatment Effect papers are at ICML 2026?

ICML 2026 has 27 Treatment Effect papers, versus 31 the year before.

How many Treatment Effect papers are at CVPR 2026?

CVPR 2026 has 17 Treatment Effect papers, versus 17 the year before.

Which conference publishes the most Treatment Effect papers?

NeurIPS, with 131 papers from 2023 to 2026.