Abstract: In the field of non-cooperative network topology inference for unmanned aerial vehicle (UAV) swarm networks, current causality discovery-based methodologies typically depend on critical ...

Department of Otorhinolaryngology, The First Hospital of China Medical University, Shenyang, Liaoning, China Purpose: To investigate whether iron metabolism exerts a causal influence on chronic ...

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...

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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 ...

Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...

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: 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 ...

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 ...

oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast ...

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 ...