Research map / Probabilistic and scientific modeling
Treatment effects: research map
421 accepted papers on Treatment effects in Probabilistic and scientific modeling, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 2 clusters and 6 approaches. The busiest year so far is 2026.
Within Probabilistic and scientific modeling, its share shrank from 6.4% in 2023–24 to 5.4% in 2025–26 (131 → 164 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
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Approaches and key papers
causal effects · causal inference · iv · 215 papers
Approaches in this cluster:
- Proximal and deep causal effect estimation (105 papers)
Estimates treatment effects with proximal learning, transformers and balancing for structured or continuous treatments. - Latent-variable causal inference (91 papers)
Infers individual effects using deep latent-variable and structural-equation models. - Instrumental variable estimation (19 papers)
Estimates causal effects with instrumental variables, including invalid and conditional instruments.
Most cited and most cited since 2024:
- Causal Effect Inference with Deep Latent-Variable Models (NeurIPS 2017 · 281 citations)
- Recommendations as Treatments: Debiasing Learning and Evaluation (ICML 2016 · 138 citations)
- Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment (AAAI 2024 · 11 citations)
- Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders (AAAI 2024 · 10 citations)
treatment effects · heterogeneous treatment · average treatment · 206 papers
Approaches in this cluster:
- Meta-learners and partial identification (78 papers)
Estimates conditional treatment effects with proximal learning and bounds under partial identification. - Benchmarking treatment effect models (77 papers)
Evaluates limits and representation learning methods for heterogeneous treatment effect estimation. - Distributional treatment effects (51 papers)
Estimates distributional and kernel treatment effects with doubly robust tests.
Most cited and most cited since 2024:
- GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets (ICLR 2018 · 179 citations)
- Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes (NeurIPS 2017 · 152 citations)
- Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation (AAAI 2024 · 8 citations)
- Probabilities of Causation with Nonbinary Treatment and Effect (AAAI 2024 · 6 citations)
Related topics in Probabilistic and scientific modeling
- Dynamical systems (969)
- Uncertainty and Gaussian processes (1,162)
- Molecules and proteins (1,990)
- Variational and generative sampling (2,060)
- Differential equations and PDEs (614)
- Causal discovery (830)
- Bayesian optimization (397)