Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...
Background and Aims: Obstructive coronary artery disease (CAD) can lead to myocardial infarction or cardiac death. The accuracy of conventional risk prediction models is limited, leading to excessive ...
High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
An electronic warfare (EW) team in a hide site deep in the woods notices a suspected enemy frequency. At the same time, an aerial EW platform using the same equipment finds the same signal. With both ...
Traditional path planning algorithms often face problems such as local optimum traps and low monitoring efficiency in agricultural UAV operations, making it difficult to meet the operational ...
School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China ...
This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs. Over the past 6 hours, it has been determined flaky in 16 workflow(s) with 32 failures ...
Abstract: Synthetic consortia represent an emerging research area in synthetic biology, promising to solve various industrial challenges through the metabolic diversity, division of labor, and spatial ...
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