A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.
Abstract: Causal inference and root cause analysis play a crucial role in network performance evaluation and optimization by identifying critical parameters and explaining how the configuration ...
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What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...
Cybersecurity researchers have uncovered critical remote code execution vulnerabilities impacting major artificial intelligence (AI) inference engines, including those from Meta, Nvidia, Microsoft, ...
Background: Traditional congenital heart surgery quality assessments rely on indirect standardization via regression, which can be complicated by heterogeneity in case-mix, surgical volume, and low ...
Abstract: Recent progress in unmanned aerial vehicle (UAV) facilitates the promising low-altitude air city transport, which has high potential to alleviate traffic congestion but simultaneously ...
Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...
In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting ...
1 Department of Orthopedics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China 2 Department of Pharmacy, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, ...
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