Differentiable multi-target causal bayesian experimental design

P Tigas, Y Annadani, DR Ivanova… - International …, 2023 - proceedings.mlr.press
We introduce a gradient-based approach for the problem of Bayesian optimal experimental
design to learn causal models in a batch setting—a critical component for causal discovery …

Differentiable multi-target causal bayesian experimental design

Y Annadani, P Tigas, DR Ivanova, A Jesson… - arxiv preprint arxiv …, 2023 - arxiv.org
We introduce a gradient-based approach for the problem of Bayesian optimal experimental
design to learn causal models in a batch setting--a critical component for causal discovery …

Efficient Experimentation for Estimation of Continuous and Discrete Conditional Treatment Effects

M Razzak, P Tigas, A Jesson, Y Gal, U Shalit - NeurIPS 2024 Workshop on … - openreview.net
Accurately estimating personalized treatment effects often demands substantial data,
incurring high costs across diverse applications such as personalized advertisement …