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

106 papers, page 2 of 3

51. ICML 2024From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
52. ICML 2024Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints
53. ICML 2024Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
54. ICML 2024Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
55. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
56. ICML 2024Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
57. ICML 2024Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
58. ICML 2024Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
59. ICML 2024On Least Square Estimation in Softmax Gating Mixture of Experts
60. ICML 2024Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
61. ICML 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect
62. ICML 2024Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
63. ICML 2024Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
64. ICML 2024Predicting Dose-Response Curves with Deep Neural Networks
65. ICML 2024Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
66. ICML 2024Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
67. ICML 2024S$\Omega$I: Score-based O-INFORMATION Estimation
68. ICML 2024Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
69. ICML 2024Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
70. ICML 2024Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
71. ICML 2024Sub-token ViT Embedding via Stochastic Resonance Transformers
72. ICML 2024The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
73. ICML 2024Transitional Uncertainty with Layered Intermediate Predictions
74. ICML 2024Uncertainty Estimation by Density Aware Evidential Deep Learning
75. NeurIPS 2024A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding
76. NeurIPS 2024An effective framework for estimating individualized treatment rules
77. NeurIPS 2024Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
78. NeurIPS 2024Breaking the curse of dimensionality in structured density estimation
79. NeurIPS 2024Capturing the denoising effect of PCA via compression ratio
80. NeurIPS 2024Causal Effect Identification in a Sub-Population with Latent Variables
81. NeurIPS 2024Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects
82. NeurIPS 2024Conditional Density Estimation with Histogram Trees
83. NeurIPS 2024Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
84. NeurIPS 2024Conditional Outcome Equivalence: A Quantile Alternative to CATE
85. NeurIPS 2024DiffPO: A causal diffusion model for learning distributions of potential outcomes
86. NeurIPS 2024Dynamic Subgroup Identification in Covariate-adjusted Response-adaptive Randomization Experiments
87. NeurIPS 2024End-To-End Causal Effect Estimation from Unstructured Natural Language Data
88. NeurIPS 2024Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data
89. NeurIPS 2024Hierarchical and Density-based Causal Clustering
90. NeurIPS 2024Higher-Order Causal Message Passing for Experimentation with Complex Interference
91. NeurIPS 2024Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
92. NeurIPS 2024Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
93. NeurIPS 2024Local to Global: Learning Dynamics and Effect of Initialization for Transformers
94. NeurIPS 2024LT-Defense: Searching-free Backdoor Defense via Exploiting the Long-tailed Effect
95. NeurIPS 2024Navigating the Effect of Parametrization for Dimensionality Reduction
96. NeurIPS 2024On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity
97. NeurIPS 2024Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
98. NeurIPS 2024RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting
99. NeurIPS 2024Statistical-Computational Trade-offs for Density Estimation
100. NeurIPS 2024Structured Learning of Compositional Sequential Interventions

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.