Essays about: "Bayesian model averaging"

Showing result 1 - 5 of 8 essays containing the words Bayesian model averaging.

  1. 1. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction

    University essay from KTH/Matematisk statistik

    Author : Sabina Syed; Josefin Stenberg; [2023]
    Keywords : Adversarial Convex Regularization; Computer Vision; Cone Beam Computed Tomography; Convolutional Neural Networks; Deep Learning; Image Reconstruction; Adversarial Convex Regularization; Bildrekonstruktion; Datorseende; Djupinlärning; Faltningsnätverk; Volymtomografi;

    Abstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE

  3. 2. Active Learning for Extractive Question Answering

    University essay from Linköpings universitet/Statistik och maskininlärning

    Author : Salvador Marti Roman; [2022]
    Keywords : Machine Learning; Deep Learning; Active Learning; Natural Language Processing; NLP; Question Answering; Transformers; Uncertainty; Language Models;

    Abstract : Data labelling for question answering tasks (QA) is a costly procedure that requires oracles to read lengthy excerpts of texts and reason to extract an answer for a given question from within the text. QA is a task in natural language processing (NLP), where a majority of recent advancements have come from leveraging the vast corpora of unlabelled and unstructured text available online. READ MORE

  4. 3. Subsampling Strategies for Bayesian Variable Selection and Model Averaging in GLM and BGNLM

    University essay from Stockholms universitet/Statistiska institutionen

    Author : Jon Lachmann; [2021]
    Keywords : Bayesian model averaging; subsampling; GLM; BGNLM; IRLS; Optimisation;

    Abstract : Bayesian Generalized Nonlinear Models (BGNLM) offer a flexible alternative to GLM while still providing better interpretability than machine learning techniques such as neural networks. In BGNLM, the methods of Bayesian Variable Selection and Model Averaging are applied in an extended GLM setting. READ MORE

  5. 4. On Optimal Sample-Frequency and Model-Averaging Selection When Predicting Realized Volatility

    University essay from Stockholms universitet/Nationalekonomiska institutionen

    Author : Joakim Gartmark; [2017]
    Keywords : ;

    Abstract : Predicting volatility of financial assets based on realized volatility has grown popular in the literature due to its strong prediction power. Theoretically, realized volatility has the advantage of being free from measurement error since it accounts for intraday variation that occurs on high frequencies in financial assets. READ MORE

  6. 5. Prediction of Linear Models: Application of Jackknife Model Averaging

    University essay from Uppsala universitet/Statistiska institutionen

    Author : Geroukis Asterios; [2016]
    Keywords : ;

    Abstract : When using linear models, a common practice is to find the single best model fit used in predictions. This on the other hand can cause potential problems such as misspecification and sometimes even wrong models due to spurious regression. READ MORE