Essays about: "Grafneurala nätverk"

Found 5 essays containing the words Grafneurala nätverk.

1. 1. Cyber Threat Detection using Machine Learning on Graphs : Continuous-Time Temporal Graph Learning on Provenance Graphs

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

   Author : Jakub Reha; [2023]
   Keywords : Graph neural networks; Temporal graphs; Benchmark datasets; Anomaly detection; Heterogeneous graphs; Provenance graphs; Grafiska neurala nätverk; temporala grafer; benchmark-datauppsättningar; anomalidetektering; heterogena grafer; härkomstgrafer;

   Abstract : Cyber attacks are ubiquitous and increasingly prevalent in industry, society, and governmental departments. They affect the economy, politics, and individuals. READ MORE

3. 2. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks

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

   Author : Lucas Alava Peña; [2023]
   Keywords : Instruction Scheduling; Deep reinforcement Learning; Compilers; Graph Convolutional Networks; Schemaläggning av instruktioner; Deep Reinforcement Learning; kompilatorer; grafkonvolutionella nätverk;

   Abstract : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. READ MORE

4. 3. Graph Neural Networks for Article Recommendation based on Implicit User Feedback and Content

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

   Author : Márk Bereczki; [2021]
   Keywords : Recommender systems; Implicit recommendation; Graph neural networks; Simple Graph Convolution; Natural language processing; Rekommendationssystem; Implicit rekommendation; Grafneurala nätverk; Simple Graph Convolution; Naturlig språkbehandling;

   Abstract : 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. READ MORE

5. 4. A Study of the Loss Landscape and Metastability in Graph Convolutional Neural Networks

   University essay from KTH/Matematisk statistik

   Author : Sofia Larsson; [2020]
   Keywords : Graph neural networks; Graph convolutional neural networks; Loss landscape; Gradient descent; Stochastic gradient descent; Stochastic gradient Langevin dynamics; Grafneurala nätverk; grafiska faltningsnätverk; lösningslandskap; gradientmetoder; stokastiska gradientmetoder; stokastisk gradient Langevin dynamik;

   Abstract : Many novel graph neural network models have reported an impressive performance on benchmark dataset, but the theory behind these networks is still being developed. In this thesis, we study the trajectory of Gradient descent (GD) and Stochastic gradient descent (SGD) in the loss landscape of Graph neural networks by replicating Xing et al. READ MORE

6. 5. Pooling strategies for graph convolution neural networks and their effect on classification

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

   Author : Jindong Wu; [2020]
   Keywords : ;

   Abstract : With the development of graph neural networks, this novel neural network has been applied in a broader and broader range of fields. One of the thorny problems researchers face in this field is selecting suitable pooling methods for a specific research task from various existing pooling methods. READ MORE