Essays about: "Missing not at Random"

Showing result 1 - 5 of 12 essays containing the words Missing not at Random.

  1. 1. Detecting Metro Service Disruptions and Predicting their Spillover Effects throughout the Network using GTFS and Large-Scale Vehicle Location Data

    University essay from KTH/Transportplanering

    Author : WeiZhi Michelle Teo; [2023]
    Keywords : ;

    Abstract : One of the top factors that influence commuters’ satisfaction level with public transport is the punctuality of the service. Commuters rely on public transport to get them from their origin to destination on time and any form of delay will incur additional cost to both the commuters as well as the public transport operators. READ MORE

  3. 2. Diffusion Models for Video Prediction and Infilling : Training a conditional video diffusion model for arbitrary video completion tasks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Tobias Höppe; [2022]
    Keywords : Diffusion; Video prediction and infilling; Conditional generation; Diffusion; Videoförutsägelse och ifyllnad; Villkorad generation;

    Abstract : To predict and anticipate future outcomes or reason about missing information in a sequence is a key ability for agents to be able to make intelligent decisions. This requires strong temporally coherent generative capabilities. READ MORE

  4. 3. Missing Data - A Gentle Introduction

    University essay from Uppsala universitet/Statistiska institutionen

    Author : Vilgot Österlund; [2020]
    Keywords : Missing data; Small samples; Multiple imputation; Maximum likelihood; Listwise deletion; Missing at random; Missing completely at random; Linear regression; Logistic regression.;

    Abstract : This thesis provides an introduction to methods for handling missing data. A thorough review of earlier methods and the development of the field of missing data is provided. The thesis present the methods suggested in today’s literature, multiple imputation and maximum likelihood estimation. READ MORE

  5. 4. Object Tracking Achieved by Implementing Predictive Methods with Static Object Detectors Trained on the Single Shot Detector Inception V2 Network

    University essay from Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

    Author : Richard Dan William Barkman; [2019]
    Keywords : Supervised Machine Learning; Hyperparameter Optimisation; Convolutional Neural Networks; Lagrangian Mechanics; Predictive Methods;

    Abstract : In this work, the possibility of realising object tracking by implementing predictive methods with static object detectors is explored. The static object detectors are obtained as models trained on a machine learning algorithm, or in other words, a deep neural network. READ MORE

  6. 5. Deep Learning techniques for classification of data with missing values

    University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Author : Leo Zethraeus; [2019]
    Keywords : Deep Learning; VAE; Variational Autoencoder; Missing Data; Artificial Neural Networks; CNN; Multiple Imputation; Physics and Astronomy;

    Abstract : Two deep learning techniques for classification on corrupt data are investigated and compared by performance. A simple imputation before classification is compared to imputation using a Variational Autoencoder (VAE). READ MORE