Sökning: "gaussiska processer"
Visar resultat 6 - 10 av 19 uppsatser innehållade orden gaussiska processer.
6. Early-Stage Prediction of Lithium-Ion Battery Cycle Life Using Gaussian Process Regression
Master-uppsats, KTH/Matematisk statistikSammanfattning : Data-driven prediction of battery health has gained increased attention over the past couple of years, in both academia and industry. Accurate early-stage predictions of battery performance would create new opportunities regarding production and use. LÄS MER
7. Image Distance Learning for Probabilistic Dose–Volume Histogram and Spatial Dose Prediction in Radiation Therapy Treatment Planning
Master-uppsats, KTH/Matematisk statistikSammanfattning : Construction of radiotherapy treatments for cancer is a laborious and time consuming task. At the same time, when presented with a treatment plan, an oncologist can quickly judge whether or not it is suitable. This means that the problem of constructing these treatment plans is well suited for automation. LÄS MER
8. Gaussian Process Methods for Estimating Radio Channel Characteristics
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Gaussian processes (GPs) as a Bayesian regressionmethod have been around for some time. Since proven advant-ageous for sparse and noisy data, we explore the potential ofGaussian process regression (GPR) as a tool for estimating radiochannel characteristics. LÄS MER
9. Automatic Generation of Patient-specific Gamma Knife Treatment Plans for Vestibular Schwannoma Patients
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis a new fully automatic process for radiotherapy treatment planning with the Leksell Gamma Knife is implemented and evaluated: First, a machine learning algorithm is trained to predict the desired dose distribution, then a convex optimization problem is solved to find the optimal Gamma Knife configuration using the prediction as the optimization objective. The method is evaluated using Bayesian linear regression, Gaussian processes and convolutional neural networks for the prediction. LÄS MER
10. Automatic Generation of Patient-specific Gamma Knife Treatment Plans for Vestibular Schwannoma Patients
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis a new fully automatic process for radiotherapy treatment planning with the Leksell Gamma Knife is implemented and evaluated: First, a machine learning algorithm is trained to predict the desired dose distribution, then a convex optimization problem is solved to find the optimal Gamma Knife configuration using the prediction as the optimization objective. The method is evaluated using Bayesian linear regression, Gaussian processes and convolutional neural networks for the prediction. LÄS MER