Essays about: "Graph Convolutional Neural Network"
Showing result 1 - 5 of 32 essays containing the words Graph Convolutional Neural Network.
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1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE
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2. Reconstruction of Radio Detector Data using Graph Neural Networks
University essay from Uppsala universitet/HögenergifysikAbstract : The current neutrino detectors have been able to detect neutrinos in the range of TeV to 100 PeV, however, ultra high energy (UHE) neutrinos above 100 PeV still remain to be detected. A new neutrino detector, the RNO-G, is currently being constructed in Greenland with the purpose of detecting the first UHE neutrinos using radio antennas capable of measuring the Askaryan pulse generated after a neutrino interaction with the ice molecules. READ MORE
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3. Decreasing Training Time of Reinforcement Learning Agents for Remote Tilt Optimization using a Surrogate Neural Network Approximator
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : One possible application of reinforcement learning in the telecommunication field is antenna tilt optimization. However, one of key challenges we face is that the use of handcrafted simulators as environments to provide information for agents is often time-consuming regarding training reinforcement learning agents. READ MORE
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4. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. READ MORE
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5. Comparison of deep learning and model-based approaches for spatial profiling of the immune tumor environment on multiplex image data
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The demographics of the tumor microenvironment (TME) impact the Immunotherapy responses for lung cancer patients. Given the heterogeneity of immune cells present within TME, the distribution patterns of different subpopulations of T-cells can be exploited to predict short-term or long-term survival of lung cancer patients. READ MORE
