Sökning: "Graph Representation Learning"

Visar resultat 1 - 5 av 24 uppsatser innehållade orden Graph Representation Learning.

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

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Sammanfattning : Cyber attacks are ubiquitous and increasingly prevalent in industry, society, and governmental departments. They affect the economy, politics, and individuals. LÄS MER

3. 2. Intersecting Graph Representation Learning and Cell Profiling : A Novel Approach to Analyzing Complex Biomedical Data

   Master-uppsats, Uppsala universitet/Institutionen för farmaceutisk biovetenskap

   Författare :Nima Chamyani; [2023]
   Nyckelord :Graph representation learning; Cell profiling; Biological systems; Network medicine; Graphs; Machine learning techniques; Graph neural networks GNNs ; Protein-Compound-Pathway interactions; Biomarkers; Drug discovery;

   Sammanfattning : 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

4. 3. Highway Traffic Forecasting with the Diffusion Model : An Image-Generation Based Approach

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Pengnan Chi; [2023]
   Nyckelord :Diffusion model; Traffic forecasting; Generative model; Image processing; Spatial temporal modelling; Diffusionsmodell; Trafikprognos; Generativ modell; Bildbehandling; Rumsligtemporal modellering;

   Sammanfattning : Forecasting of highway traffic is a common practice for real traffic information system, and is of vital importance to traffic management and control on highways. As a typical time-series forecasting task, we want to propose a deep learning model to map the historical sensory traffic values (e.g., speed, flow) to future traffic forecasts. LÄS MER

5. 4. Modelling Cyber Security of Networks as a Reinforcement Learning Problem using Graphs : An Application of Reinforcement Learning to the Meta Attack Language

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Sandor Berglund; [2022]
   Nyckelord :Attack graphs; reinforcement learning; graph neural networks; Meta Attack Language; MAL; deepQ-learning DQN ; Attackgrafer; förstärningsinlärning; artificiella neuronnät; grafneuronnät; djup Qinlärning; Meta Attack Language; MAL;

   Sammanfattning : ICT systems are part of the vital infrastructure in today’s society. These systems are under constant threat and efforts are continually being put forth by cyber security experts to protect them. By applying modern AI methods, can these efforts both be improved and alleviated of the cost of expert work. LÄS MER

7. 5. An unsupervised method for Graph Representation Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Yi Ren; [2022]
   Nyckelord :Graph Representation Learning; unsupervised learning; machine learning;

   Sammanfattning : Internet services, such as online shopping and chat apps, have been spreading significantly in recent years, generating substantial amounts of data. These data are precious for machine learning and consist of connections between different entities, such as users and items. LÄS MER