Sökning: "Graph neural networks"
Visar resultat 1 - 5 av 37 uppsatser innehållade orden Graph neural networks.
- Master-uppsats, Göteborgs universitet / Institutionen för fysik
Sammanfattning : A graph neural network (GNN) is constructed and trained with a purpose of usingit as a quantum error correction decoder for depolarized noise on the surface code.Since associating syndromes on the surface code with graphs instead of grid-likedata seemed promising, a previous decoder based on the Markov Chain Monte Carlomethod was used to generate data to create graphs. LÄS MER
- Master-uppsats, Uppsala universitet/Institutionen för farmaceutisk biovetenskap
Sammanfattning : Many people - especially during their elderly - consume multiple drugs for the treatment of complex or co-existing diseases. Identifying side effects caused by polypharmacy is crucial for reducing mortality and morbidity of the patients which will lead to improvement in their quality of life. LÄS MER
- Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildningUppsala universitet/Institutionen för informationsteknologi
Sammanfattning : The increase in demand for food has resulted in increased demand for tools that help streamline plant breeding process in order to create new varieties of crops. Identifying the underlying genetic mechanism of favourable characteristics is essential in order to make the best breeding decisions. LÄS MER
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Recommender systems are widely used in websites and applications to help users find relevant content based on their interests. Graph neural networks achieved state- of-the- art results in the field of recommender systems, working on data represented in the form of a graph. LÄS MER
- Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi
Sammanfattning : This report is done in collaboration with WirelessCar for the master of science thesis at Halmstad University. Many different parameters influence fuel consumption. The objective of the report is to evaluate if Graph neural networks are a practical model to perform fuel consumption prediction on areas. LÄS MER