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Contrastive learning has been widely used in graph representation learning, which extracts node or graph representations by contrasting positive and negative node pairs. It requires node ...
In recent years, unsupervised graph representation learning based on graph encoders has made significant progress. However, the existing methods have three shortcomings. First, the existing method ...
In “Exploring Inclusivity in AI Education: Perceptions and Pathways for Diverse Learners” (2024), Dr. Daniel Chang and his co-author drew from Adaptive and Inclusive AI Learning theory (AIAL) and a ...
Free access Gastrointestinal Cancer—Gastroesophageal, Pancreatic, and Hepatobiliary May 28, 2025 Adaptive organoid-based precision therapy study in pancreatic cancer (ADOPT): A phase II single-arm ...
Reinforcement learning (RL) is renowned for its proficiency in modeling sequential tasks and adaptively learning latent data patterns. Deep learning models have been extensively explored and adopted ...
Using adaptive technology, ALEKS provides personalized learning in basic math through calculus to help students qualify to take more advanced courses. “When students arrive on campus better prepared ...
We consider the problem of learning graphs from smooth signals in an online fashion. A major challenge of this task is that the underlying graph may be time-varying. Existing works typically assume ...
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