Essays about: "graph neural networks"

Showing result 16 - 20 of 82 essays containing the words graph neural networks.

1. 16. Estimation of Voltage Drop in Power Circuits using Machine Learning Algorithms : Investigating potential applications of machine learning methods in power circuits design

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Dimitrios Koutlis; [2023]
   Keywords : Voltage drop estimation; Application-specific Integrated Circuits ASICs ; Machine learning algorithms; XGBoost; Convolutional Neural Networks; Graph Neural Networks; Power circuit optimization; Uppskattning av spänningsfall; applikationsspecifika integrerade kretsar ASIC ; maskininlärningsalgoritmer; XGBoost; konvolutionella neurala nätverk; optimering av strömkretsar;

   Abstract : 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. READ MORE

3. 17. The Applicability and Scalability of Graph Neural Networks on Combinatorial Optimization

   University essay from KTH/Matematik (Avd.)

   Author : Peder Hårderup; [2023]
   Keywords : applied mathematics; combinatorial optimization; machine learning; graph neural networks; scalability; tillämpad matematik; kombinatorisk optimering; maskininlärning; grafiska neurala nätverk; skalbarhet;

   Abstract : 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. READ MORE

4. 18. Graph Attention Networks for Link Prediction in Semantic Word Grouping

   University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

   Author : Anton Gollbo; [2023]
   Keywords : ;

   Abstract : 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. READ MORE

5. 19. Trigger-Level Multiple Electron Event Classification with LDMX using Artificial Neural Networks

   University essay from Lunds universitet/Partikel- och kärnfysik; Lunds universitet/Fysiska institutionen

   Author : Jacob Lindahl; [2023]
   Keywords : LDMX; ANN; CNN; GNN; RNN; DM; Physics and Astronomy;

   Abstract : Artificial neural networks is a powerful tool for classifying and identifying patterns in large amounts of data. One of the possible tasks of these networks is classification of data into categories. READ MORE

6. 20. Software Fault Detection in Telecom Networks using Bi-level Federated Graph Neural Networks

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Rémi Bourgerie; [2023]
   Keywords : 5G 4G; Federated Learning; Graoh Learning; Graph-based Federated Learning; Temporal Graph Neural Networks; Time Series; Anomaly Detection; Fault Detection; 5G 4G; Federerat lärande; Graf lärande; Grafbaserat federerat lärande; Temporal Graph Neural Networks; Tidsserier; Upptäckt av anomalier; Upptäckt av fel;

   Abstract : The increasing complexity of telecom networks, induced by the recent development of 5G, is a challenge for detecting faults in the telecom network. In addition to the structural complexity of telecommunication systems, data accessibility has become an issue both in terms of privacy and access cost. READ MORE