Mixed Supervised Graph Contrastive Learning for Recommendation
Recommender systems (RecSys) play a vital role in online platforms, offering users personalized suggestions amidst vast information. Graph contrastive learning aims to learn from high-order collaborative filtering signals with unsupervised augmentation ...
Yang, Liangwei +6 more
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Chest Equivalent Dose as a Symbolic Radiation Communication Tool: Leadership Implications for Nurses' Knowledge, Anxiety, and Risk Attribution. [PDF]
Ayasrah M, Alrashdan YG.
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Factors and Challenges Affecting the Research Output of Medical Students: A Mixed-Methods Study. [PDF]
Awadh AA, Khan MA.
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Unit-time Job-shop Scheduling via Mixed Graph Coloring
International audienceA unit-time scheduling problem with makespan criterion may be interpreted as an optimal coloring of the vertices of a mixed graph, where the number of colors is minimal.
Sotskov, Yuri +2 more
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Turning failure into success: how artificial intelligence can help personalize therapies and re-use patient data. [PDF]
Abbracchio MP, Damiani E.
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Exploring Neurofunctional Phase Transition Patterns in Autism Spectrum Disorder via Thermodynamics Parameters. [PDF]
Qin D, Chen Y, Kuruoglu EE.
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Decentralized graph attention multi-agent reinforcement learning for adaptive urban traffic routing. [PDF]
Mahmoud M +3 more
europepmc +1 more source
ExposoGraph: An Interactive Platform for Carcinogen Bioactivation and Detoxification Pathway Visualization. [PDF]
Kazi JU, Pienta KJ.
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GPLD1 is a scavenger carrier mediating lysosomal degradation of extracellular aberrant proteins. [PDF]
Tsuchiya M, Yagishita Y, Itakura E.
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This paper develops a quantitative, graph-theoretic method for analysing systems of institutions. With an application to the agricultural innovation system of Azerbaijan, the method is illustrated in detail.
Karimov, Fuad +2 more
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