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Publications associées (30)
Scalable maximal subgraph mining with backbone-preserving graph convolutions
Karl Aberer, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên
Maximal subgraph mining is increasingly important in various domains, including bioinformatics, genomics, and chemistry, as it helps identify common characteristics among a set of graphs and enables their classification into different categories. Existing ...
ELSEVIER SCIENCE INC2023SEISMIC VULNERABILITY ASSESSMENT AT LARGE SCALE CASE STUDY: THE CANTON OF BASEL-STADT
Large-scale seismic risk assessment requires knowledge of the vulnerability of buildings. Under the action of an earthquake, buildings with different properties also behave differently. Since it is not possible to analyze each building individually, it is ...
2020Using Educational Data From Teaching And Learning To Inform Teachers’ Reflective Educational Design In Inquiry-Based STEM Education
Denis Gillet, Maria Jesus Rodriguez Triana
Science, Technology, Engineering and Mathematics (STEM) education is recognized as a top priority for school education worldwide and Inquiry-based teaching and learning is identified as one of the most dominant approaches. To effectively engage individual ...
2019Incremental Learning Meets Reduced Precision Networks
Hardware accelerators for Deep Neural Networks (DNNs) that use reduced precision parameters are more energy efficient than the equivalent full precision networks. While many studies have focused on reduced precision training methods for supervised networks ...
2019