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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.

168,878 papers · 148 categories

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2 results for “M-Bias”

A Bayesian Solution to the M-Bias Problemstat.ML

Bayesian method tackles M-Bias in causal inference.

problem M-Bias causes incorrect causal effect inference when adjusting for variables.

method Bayesian approach to replicate Pearl's solution while conditioning on all variables.

result Bayesian solution to M-Bias problem is possible.

Bayesian statistics causal inference M-Bias causal graphical models probabilistic graphical models

2019-06-17abs ↗pdf ↗

Causal Inference with the Napkin Graphstat.ME

A new causal graph framework identifies treatment effects without adjusting for confounders.

problem Invalid identification of causal effects due to unmeasured confounders.

method Developed the Napkin graph to identify causal effects through a ratio of g-formulas, using influence-function-based estimators.

result Demonstrated substantial efficiency gains in estimating causal effects using the Napkin graph.

Causal inference Napkin graph g-formula Verma constraint Efficiency bounds

2025-12-22abs ↗pdf ↗