Web: http://arxiv.org/abs/2206.08363

June 17, 2022, 1:11 a.m. | Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar

cs.LG updates on arXiv.org arxiv.org

Estimating personalized effects of treatments is a complex, yet pervasive
problem. To tackle it, recent developments in the machine learning (ML)
literature on heterogeneous treatment effect estimation gave rise to many
sophisticated, but opaque, tools: due to their flexibility, modularity and
ability to learn constrained representations, neural networks in particular
have become central to this literature. Unfortunately, the assets of such black
boxes come at a cost: models typically involve countless nontrivial operations,
making it difficult to understand what they …

arxiv benchmarking interpretability lg models treatment

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