Sökning: "Bayesianska neurala nätverk"
Visar resultat 1 - 5 av 13 uppsatser innehållade orden Bayesianska neurala nätverk.
1. LDPC DropConnect
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Machine learning is a popular topic that has become a scientific research tool in many fields. Overfitting is a common challenge in machine learning, where the model fits the training data too well and performs poorly on new data. LÄS MER
2. Non-Bayesian Out-of-Distribution Detection Applied to CNN Architectures for Human Activity Recognition
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Human Activity Recognition (HAR) field studies the application of artificial intelligence methods for the identification of activities performed by people. Many applications of HAR in healthcare and sports require the safety-critical performance of the predictive models. LÄS MER
3. Inverse Uncertainty Quantification for Sounding Rocket Dispersion
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Sounding rocket impact points are subject to dispersion due to uncertainties in simulation model parameters and perturbations of the rocket trajectory during flight. Estimating the area of dispersion assumes that associated model uncertainties and magnitude of perturbations have already been inferred. LÄS MER
4. Deep Bayesian Neural Networks for Prediction of Insurance Premiums
Master-uppsats, KTH/Matematisk statistikSammanfattning : In this project, the problem concerns predicting insurance premiums and particularly vehicle insurance premiums. These predictions were made with the help of Bayesian Neural Networks (BNNs), a type of Artificial Neural Network (ANN). The central concept of BNNs is that the parameters of the network follow distributions, which is beneficial. LÄS MER
5. Deep Bayesian Neural Networks for Prediction of Insurance Premiums
Master-uppsats, KTH/Matematisk statistikSammanfattning : In this project, the problem concerns predicting insurance premiums and particularly vehicle insurance premiums. These predictions were made with the help of Bayesian Neural Networks (BNNs), a type of Artificial Neural Network (ANN). The central concept of BNNs is that the parameters of the network follow distributions, which is beneficial. LÄS MER