Essays about: "gaussisk blandningsmodell"

Showing result 1 - 5 of 6 essays containing the words gaussisk blandningsmodell.

  1. 1. Regression with Bayesian Confidence Propagating Neural Networks

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

    Author : Raghav Rajendran Bongole; [2023]
    Keywords : Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

    Abstract : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. READ MORE

  3. 2. Neural Ordinary Differential Equations for Anomaly Detection

    University essay from KTH/Matematisk statistik

    Author : Jón Hlöðver Friðriksson; Erik Ågren; [2021]
    Keywords : Anomaly detection; Neural ordinary differential equations; Statistical modelling; Autoregression; Variational autoencoder; Multivariate time series; Anomalidetektion; Neurala ordinära differentialekvationer; Statistisk modellering; Autoregression; Variational autoencoder; Multivariat tidsserie;

    Abstract : Today, a large amount of time series data is being produced from a variety of different devices such as smart speakers, cell phones and vehicles. This data can be used to make inferences and predictions. Neural network based methods are among one of the most popular ways to model time series data. READ MORE

  4. 3. Incorporating Metadata Into the Active Learning Cycle for 2D Object Detection

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

    Author : Karsten Stadler; [2021]
    Keywords : Active learning; Deep Learning; Object detection; Metadata; Nuscenes Nuimages; Gaussian mixture model; Rejection sampling; Monte-Carlo methods; Aktiv Inlärning; Djupinlärning; Objektdetektering; metadata; Nuscenes Nuimages; Gaussisk blandingsmodell; Rejection sampling; Monte-Carlo metoder;

    Abstract : In the past years, Deep Convolutional Neural Networks have proven to be very useful for 2D Object Detection in many applications. These types of networks require large amounts of labeled data, which can be increasingly costly for companies deploying these detectors in practice if the data quality is lacking. READ MORE

  5. 4. Capturing Tail Risk in a Risk Budgeting Model

    University essay from KTH/Matematisk statistik

    Author : Filip Lundin; Markus Wahlgren; [2020]
    Keywords : ;

    Abstract : Risk budgeting, in contrast to conventional portfolio management strategies, is all about distributing the risk between holdings in a portfolio. The risk in risk budgeting is traditionally measured in terms of volatility and a Gaussian distribution is commonly utilized for modeling return data. READ MORE

  6. 5. Speaker Diarization System for Call-center data

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

    Author : Yi Li; [2020]
    Keywords : MFCC-vector Speaker Diarization; Speaker Verification; Voice Active Detection; Gaussian Mixture Model; Hierarchy Clustering; MFCC-vektor Högtalardarisering; Högtalarverifiering; Röstaktiv detektering; Gaussisk blandningsmodell; Hierarkikluster;

    Abstract : To answer the question who spoke when, speaker diarization (SD) is a critical step for many speech applications in practice. The task of our project is building a MFCC-vector based speaker diarization system on top of a speaker verification system (SV), which is an existing Call-centers application to check the customer’s identity from a phone call. READ MORE