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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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3 results for “TARNet”

Advantages and limitations in the use of transfer learning for individual treatment effects in causal machine learningstat.ML

Transfer learning improves causal model estimates in small samples.

problem Challenges in estimating individual treatment effects (ITE) from small datasets.

method Treatment Agnostic Representation Networks (TARNet) with transfer learning (TL-TARNet).

result Transfer learning reduces ITE error and bias in small samples.

transfer learning causal machine learning individual treatment effects small datasets firewood collection

2025-12-18abs ↗pdf ↗

Representation Learning for Semiparametric Causal Mediation Analysis under No Essential Heterogeneitystat.ML

A method combines deep learning and G-estimation for causal mediation analysis.

problem Estimating structural mediation parameters under unmeasured confounding.

method UNIT method using TARNet for representation learning and G-estimation.

result Improved precision of structural parameter estimator through better representation learning.

causal mediation representation learning G-estimation TARNet structural parameters

2026-07-12abs ↗pdf ↗

MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedbackstat.ML

MOCA uses modular attention to estimate causal effects from complex data.

problem Estimating causal effects from observational data with complex, non-linear, and high-dimensional treatment and outcome mechanisms.

method MOCA is a transformer-based framework that separates treatment and outcome modeling through modular design and one-way attention mechanism, with cutting-feedback to prevent outcome influence on treatment representations.

result MOCA outperforms classical estimators and machine learning approaches across various simulated and real-world scenarios.

Transformer Causal Inference One-way Attention Confounding Adjustment Machine Learning

2026-04-25abs ↗pdf ↗