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4 papers
Identification of Average Causal Effects in Confounded Additive Noise Models
Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
Additive noise models (ANMs) are an important setting studied in causal inference. Most of the existing works on ANMs assume causal sufficiency, i.e., there are no unobserved confo…
Submodular Information Selection for Hypothesis Testing with Misclassification Penalties
Jayanth Bhargav, Mahsa Ghasemi, Shreyas Sundaram
We consider the problem of selecting an optimal subset of information sources for a hypothesis testing/classification task where the goal is to identify the true state of the world…
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu +1
Causal discovery aims to uncover cause-and-effect relationships encoded in causal graphs by leveraging observational, interventional data, or their combination. The majority of exi…
Formal Methods for Autonomous Systems
Tichakorn Wongpiromsarn, Mahsa Ghasemi, Murat Cubuktepe +6
Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main buil…