Sökning: "Graph neural networks GNNs"
Visar resultat 1 - 5 av 13 uppsatser innehållade orden Graph neural networks GNNs.
1. Intersecting Graph Representation Learning and Cell Profiling : A Novel Approach to Analyzing Complex Biomedical Data
Master-uppsats, Uppsala universitet/Institutionen för farmaceutisk biovetenskapSammanfattning : In recent biomedical research, graph representation learning and cell profiling techniques have emerged as transformative tools for analyzing high-dimensional biological data. The integration of these methods, as investigated in this study, has facilitated an enhanced understanding of complex biological systems, consequently improving drug discovery. LÄS MER
2. Link Prediction Using Learnable Topology Augmentation
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Link prediction is a crucial task in many downstream applications of graph machine learning. Graph Neural Networks (GNNs) are a prominent approach for transductive link prediction, where the aim is to predict missing links or connections only within the existing nodes of a given graph. LÄS MER
3. Estimation of Voltage Drop in Power Circuits using Machine Learning Algorithms : Investigating potential applications of machine learning methods in power circuits design
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Accurate estimation of voltage drop (IR drop), in Application-Specific Integrated Circuits (ASICs) is a critical challenge, which impacts their performance and power consumption. As technology advances and die sizes shrink, predicting IR drop fast and accurate becomes increasingly challenging. LÄS MER
4. The Applicability and Scalability of Graph Neural Networks on Combinatorial Optimization
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : This master's thesis investigates the application of Graph Neural Networks (GNNs) to address scalability challenges in combinatorial optimization, with a primary focus on the minimum Total Dominating set Problem (TDP) and additionally the related Carrier Scheduling Problem (CSP) in networks of Internet of Things. The research identifies the NP-hard nature of these problems as a fundamental challenge and addresses how to improve predictions on input graphs of sizes much larger than seen during training phase. LÄS MER
5. Graph Attention Networks for Link Prediction in Semantic Word Grouping
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskapSammanfattning : Manually extracting relevant information from extensive amounts of data can betime-consuming and labour-intensive. Automating this process can allow for a shift of focus toward analysis and utilization of the extracted information, rather than allocating time and resources to data collection and preparation. LÄS MER