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stat.ML2026
Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks
Masahiro Tanaka
Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flexible regressions may capture o…
stat.ML2025
Estimating Bidirectional Causal Effects with Large Scale Online Kernel Learning
Masahiro Tanaka
In this study, a scalable online kernel learning framework is proposed for estimating bidirectional causal effects in systems characterized by mutual dependence and heteroskedastic…