The analysts working on AI projects have a crucial question: How will the interventions brought about by the AI cause the desired outcomes? To date, only about 20% of companies have managed to scale ...

Bayesian networks are probabilistic graphical models that encode conditional dependencies among variables within a directed acyclic graph. In the context of causal inference, these networks provide a ...

Accumulating evidence indicates that single neurons in the primate brain specifically encode sensorimotor experience about the self or others. Although the self-other distinction has been a major ...

The Multisensory Correlation Detector (MCD) population model consists of elementary computational units (left), each of which responds to audiovisual transients (that is, changes in the input) that ...

Abstract: In many science and engineering tasks, the goal is to learn causal models that accurately describe signal behavior. The gold standard for uncovering causal relationships is to apply external ...

ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...

Leptin, primarily secreted by adipose tissue, is a critical hormone involved in regulating energy balance and food intake by inducing satiety. Although several hormones influence satiety, leptin plays ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...

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OpenASCE (Open All-Scale Casual Engine) is a comprehensive, easy-to-use, and efficient end-to-end large-scale causal learning system. It provides causal discovery, causal effect estimation, and ...