Research map / Probabilistic and scientific modeling / Treatment effects
Instrumental variable estimation
Estimates causal effects with instrumental variables, including invalid and conditional instruments.
19 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2019–2026) · an approach in Treatment effects, keyword cluster “causal effects · causal inference · iv”
State History Tried Checklist Preprints Who Export
Where it stands
Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.
8 papers in 2023–24 and 4 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 6.1% to 2.4%.
How this is decided
A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.
How it got here
Most cited paper of each year
- 2019 · Deep Generalized Method of Moments for Instrumental Variable Analysis (NeurIPS 2019 · 56 citations)
- 2020 · A Class of Algorithms for General Instrumental Variable Models (NeurIPS 2020 · 4 citations)
- 2021 · Learning Deep Features in Instrumental Variable Regression (ICLR 2021 · 15 citations)
- 2022 · Instrumental Variable Regression with Confounder Balancing (ICML 2022)
- 2023 · Causal Inference with Conditional Instruments Using Deep Generative Models (AAAI 2023 · 18 citations)
- 2024 · Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders (AAAI 2024 · 10 citations)
- 2025 · Demystifying Spectral Feature Learning for Instrumental Variable Regression (NeurIPS 2025 · 0 citations)
- 2026 · Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression (ICML 2026 · 0 citations)
Earliest papers here
- Deep Generalized Method of Moments for Instrumental Variable Analysis (NeurIPS 2019 · 56 citations)
- A Class of Algorithms for General Instrumental Variable Models (NeurIPS 2020 · 4 citations)
- General Control Functions for Causal Effect Estimation from IVs (NeurIPS 2020 · 2 citations)
What has been tried
14 papers here report 108 measured changes (a component added, removed or swapped, compared with a baseline): helped 56%, no clear effect 13%, hurt 30%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.
Ablations in recent papers
| What was changed | Measured on | Result | Effect | Paper |
|---|---|---|---|---|
| Add CIV regression balance loss (Eq. 2) | Synthetic datasets, 6k · ACE estimation error | 0.48 ± 0.27 -> 0.14 ± 0.05; 0.40 ± 0.19 -> 0.14 ± 0.03; 0.41 ± 0.14 -> 0.12 ± 0.03 | Helped | Conditional Instrumental Variable Regression with Representation Learning for Causal Inference (ICLR 2024 · 0 citations) |
| Remove K-fold cross-fitting and train nuisance models once on the full dataset (CE-DML-IV) | Low-dimensional datasets · MSE | No clear effect | Learning Decision Policies with Instrumental Variables through Double Machine Learning (ICML 2024 · 0 citations) |
What reviewers will expect
Datasets and baselines named in the 6 papers of this approach from 2024–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.
Datasets
- IHDP · 2 of 6 papers
Baselines
- DeepIV · 2 of 6 papers
Recent preprints
Loading recent arXiv preprints…
Who publishes on it
Institutions on the most papers of this approach since 2023 (of 12 papers; from OpenAlex and the papers' affiliations).
- University of South Australia · 3 papers
Use it
Download BibTeX of 19 key papersOpen the topic in the interactive map
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Related approaches
Same keyword cluster
- Proximal and deep causal effect estimation (105 papers)
- Latent-variable causal inference (91 papers)
Elsewhere in the topic
- Meta-learners and partial identification (78 papers)
- Benchmarking treatment effect models (77 papers)
- Distributional treatment effects (51 papers)
Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).