Sökning: "Latent class models"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Latent class models.

  1. 1. Spatio-temporal analysis of COVID-19 in Västra Götaland, Sweden

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Natalia Andreeva; [2023-08-23]
    Nyckelord :;

    Sammanfattning : Spatio-temporal analysis of COVID-19 data with the two different statistical approaches is the main objective of this thesis. The first classical approach, the Endemic-Epidemic framework (Held et al., 2005) is a class of multivariate time-series models for the incidence counts, obtained from the surveillance systems. LÄS MER

  3. 2. Topological regularization and relative latent representations

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

    Författare :Alejandro García Castellanos; [2023]
    Nyckelord :Algebraic Topology; Large Language Models; Relative Representation; Representation Learning; Model Stitching; Topological DataAnalysis; Zero-shot; Algebraisk topologi; Stora språkmodeller; Relativ representation; Representationsinlärning; Modell sömmar; Topologisk dataanalys; Zero-shot;

    Sammanfattning : This Master's Thesis delves into the application of topological regularization techniques and relative latent representations within the realm of zero-shot model stitching. Building upon the prior work of Moschella et al. LÄS MER

  4. 3. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :M Asjid Tanveer; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. LÄS MER

  5. 4. An Application of LatentCF++ on Providing Counterfactual Explanations for Fraud Detection

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Maria-Sofia Giannopoulou; [2023]
    Nyckelord :counterfactuals; fraud detection; LatentCF ; autoencoder; one-dimensional convolutional neural network;

    Sammanfattning : The aim of explainable machine learning is to aid humans in understanding how exactly complex machine learning models work. Machine learning models have offered great performance in various areas. However, the mechanisms behind how the model works and how decisions are being made remain unknown. LÄS MER

  7. 5. Stochastic EM for generic topic modeling using probabilistic programming

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Robin Saberi Nasseri; [2021]
    Nyckelord :SEM; topic model; probabilistic programming; LDA; DMR; TFP;

    Sammanfattning : Probabilistic topic models are a versatile class of models for discovering latent themes in document collections through unsupervised learning. Conventional inferential methods lack the scaling capabilities necessary for extensions to large-scale applications. LÄS MER