Sökning: "Bayesian Structure Learning"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden Bayesian Structure Learning.

1. 1. Determining Protein Conformational Ensembles by Combining Machine Learning and SAXS

   Master-uppsats, KTH/Tillämpad fysik

   Författare :Samuel Eriksson Lidbrink; [2023]
   Nyckelord :AlphaFold; AlphaFold2; SAXS; protein conformational ensembles; machine learning; protein conformations; reweighting; SAXS; AlphaFold; AlphaFold2; proteinkonformationsensembler; maskininlärning; proteinkonformationer; omviktning;

   Sammanfattning : In structural biology, immense effort has been put into discovering functionally relevant atomic resolution protein structures. Still, most experimental, computational and machine learning-based methods alone struggle to capture all the functionally relevant states of many proteins without very involved and system-specific techniques. LÄS MER

3. 2. Bayesian Networks for Modelling the Respiratory System and Predicting Hospitalizations

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

   Författare :Victor Lopo Martinez; [2023]
   Nyckelord :Bayesian Networks; Structure Learning; Conditional Probability Tables; Maximum Likelihood Estimator; XGBoost; and Respiratory System; Bayesianska nätverk; Strukturinlärning; Villkorliga sannolikhetstabeller; Maximum Likelihood Estimator; XGBoost; och Andningssystemet;

   Sammanfattning : Bayesian networks can be used to model the respiratory system. Their structure indicate how risk factors, symptoms, and diseases are related and the Conditional Probability Tables enable predictions about a patient’s need for hospitalization. LÄS MER

4. 3. Causal Inference on Tactical Simulations using Bayesian Structure Learning

   Master-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

   Författare :Karl Lagerkvist Blomqvist; [2022]
   Nyckelord :Causal Inference; Bayesian Structure Learning; Do-Calculus; Tactical Simulations; Kausal Inferens; Bayesiansk Strukturinlärning; Do-Calculus; Taktiska Simuleringar;

   Sammanfattning : This thesis explores the possibility of using Bayesian Structure Learning and Do-Calculus to perform causal inference on data from tactical combat simulations provided by Saab. A four-step approach is considered whose first step is to find a Bayesian Network from the data using Bayesian Structure Learning and Probability Distribution Fitting. LÄS MER

5. 4. Unsupervised learning of data representations in brain-like neural networks

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

   Författare :Arian Javdan; [2021]
   Nyckelord :;

   Sammanfattning : Recently, there has been a growing interest in brain-plausible neural networks that closely resemble the brain’s structure. However, conventional networks do not make good models for the brain since these connections are modelled differently, hence the interest in brain-plausible networks. LÄS MER

7. 5. Sum-Product Network in the context of missing data

   Master-uppsats, KTH/Matematisk statistik

   Författare :Pierre Clavier; [2020]
   Nyckelord :Statistics; Mixture model; Probabilistic Graphical Models; Statistik; Probabilistiska grafiska modeller;

   Sammanfattning : In recent years, the interest in new Deep Learning methods has increased considerably due to their robustness and applications in many fields. However, the lack of interpretability of these models and the lack of theoretical knowledge about them raises many issues. It is in this context that sum product network models have emerged. LÄS MER