mlsanityData to 14 Oct 2026

IGC-Net for conditional average potential outcome estimation over time

arXiv 2405.21012 ↗First posted 31 May 2024cs.LG stat.MEcited by 10

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Abstract (arXiv)

Estimating potential outcomes for treatments over time based on observational data is important for personalized decision-making in medicine. However, many existing methods for this task fail to properly adjust for time-varying confounding and thus yield biased estimates. There are only a few neural methods with proper adjustments, but these have inherent limitations (e.g., division by propensity scores that are often close to zero), which result in poor performance. As a remedy, we introduce the iterative G-computation network (IGC-Net). Our IGC-Net is a novel, neural end-to-end model which adjusts for time-varying confounding in order to estimate conditional average potential outcomes (CAPOs) over time. Specifically, our IGC-Net is the first neural model to perform fully regression-based iterative G-computation for CAPOs in the time-varying setting. We evaluate the effectiveness of our IGC-Net across various experiments. In sum, this work represents a significant step towards personalized decision-making from electronic health records.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 33 of its 79 references that are in the map. First posted on arXiv 31 May 2024.

Builds on

33 of 79 references.

References · 33

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21 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 4.

10 papers.

  1. 2024Model-agnostic meta-learners for estimating heterogeneous treatment effects over timecited by 19
  2. 2025GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confoundingcited by 5
  3. 2025Overlap-weighted orthogonal meta-learner for treatment effect estimation over timecited by 3
  4. 2025DeepBlip: Estimating Conditional Average Treatment Effects Over Timecited by 2
  5. 2025An Orthogonal Learner for Individualized Outcomes in Markov Decision Processescited by 0
  6. 2025SCOPE: Sequential Causal Optimization of Process Interventionscited by 0
  7. 2026Deep Doubly Debiased Longitudinal Effect Estimation with ICE G-Computationcited by 0
  8. 2026Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Timecited by 0
  9. 2026Smooth Multi-Policy Causal Effect Estimation in Longitudinal Settingscited by 0
  10. 2026Decision-Aware Proximal Bridge Learning for Optimal Treatment Selectioncited by 0