Essays about: "Variational Autoencoders"

Showing result 1 - 5 of 11 essays containing the words Variational Autoencoders.

  1. 1. Neural networks for imputation of missing genotype data : An alternative to the classical statistical methods in bioinformatics

    University essay from Uppsala universitet/Institutionen för biologisk grundutbildning

    Author : Alfred Andersson; [2020]
    Keywords : genetics; imputation; bioinformatics; neural networks; GWAS;

    Abstract : In this project, two different machine learning models were tested in an attempt at imputing missing genotype data from patients on two different panels. As the integrity of the patients had to be protected, initial training was done on data simulated from the 1000 Genomes Project. READ MORE

  2. 2. Adaptive Reference Images for Blood Cells using Variational Autoencoders and Self-Organizing Maps

    University essay from Lunds universitet/Matematik LTH

    Author : Oscar Odestål; Anna Palmqvist Sjövall; [2020]
    Keywords : Image Analysis; Variational Autoencoder; Self-Organizing Maps; Deep Learning; Machine Learning; Microscopy; CellaVision; Microscope; Neural Networks; Blood Cells; White Blood Cells; Image Classification; Data Visualization; Clustering; Latent Space; Unsupervised Learning; Dimensionality Reduction; SOM; VAE; Mathematics and Statistics;

    Abstract : CellaVision develops automated microscopy for blood analysis. Their products can pre-classify 19 different types of white blood cells and support the medical technologist performing the final classification. CellaVision provides reference cells. READ MORE

  3. 3. Hierarchical Clustering of Time Series using Gaussian Mixture Models and Variational Autoencoders

    University essay from Lunds universitet/Matematisk statistik

    Author : Per Wilhelmsson; [2019]
    Keywords : Clustering; Deep Learning; Machine Learning; Time Series; Variational Autoencoders; Gaussian Mixture Models; Mathematics and Statistics;

    Abstract : This thesis proposes a hierarchical clustering algorithm for time series, comprised of a variational autoencoder to compress the series and a Gaussian mixture model to merge them into an appropriate cluster hierarchy. This approach is motivated by the autoencoders good results in dimensionality reduction tasks and by the likelihood framework given by the Gaussian mixture model. READ MORE

  4. 4. Attribute-Driven Generation of Drug Reviews using Deep Learning

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

    Author : Sylwester Liljegren; [2019]
    Keywords : ;

    Abstract : In the last years, the demands on different models using deep learning to generate textual data conditionally have increased, where one would like to control what textual data to generate from a deep learning model. For this purpose, a couple of models have been developed and achieved state-of-art performance in the field of generating textual data conditionally. READ MORE

  5. 5. Multivariate analysis of the parameters in a handwritten digit recognition LSTM system

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

    Author : Georgios Zervakis; [2019]
    Keywords : Deep Learning; Interpretability; Handwritten Digit Recognition; MNIST; Recurrent Neural Networks; PCA; SVD; Variational Autoencoders;

    Abstract : Throughout this project, we perform a multivariate analysis of the parameters of a long short-term memory (LSTM) system for handwritten digit recognition in order to understand the model’s behaviour. In particular, we are interested in explaining how this behaviour precipitate from its parameters, and what in the network is responsible for the model arriving at a certain decision. READ MORE