Essays about: "Deep averaging networks."

Showing result 1 - 5 of 7 essays containing the words Deep averaging networks..

  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. Neural Networks for Modeling of Electrical Parameters and Losses in Electric Vehicle

    University essay from Högskolan i Skövde/Institutionen för ingenjörsvetenskap

    Author : Yo Fujimoto; [2023]
    Keywords : Artificial neural network; machine learning; random forest; deep learning; electric vehicle; decision tree; k-nearest neighbors; permanent magnet synchronous machine;

    Abstract : Permanent magnet synchronous machines have various advantages and have showed the most superiorperformance for Electric Vehicles. However, modeling them is difficult because of their nonlinearity. READ MORE

  4. 3. 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

  5. 4. Classifying and Comparing Latent Space Representation of Unstructured Log Data.

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

    Author : Bharat Sharma; [2021]
    Keywords : Machine learning; Natural language processing; Deep learning; Classification; Supervised learning; Transformer models; Sentence embeddings; Doc2Vec; Deep averaging networks.; Maskininlärning; naturligtspråkbehandling; djupinlärning; klassificering; övervakad inlärning; transformeringsmodeller; meningsinbäddningar; Doc2Vec; djupa linjärkombinerande nätverk.;

    Abstract : This thesis explores and compares various methods for producing vector representation of unstructured log data. Ericsson wanted to investigate machine learning methods to analyze logs produced by their systems to reduce the cost and effort required for manual log analysis. READ MORE

  6. 5. Federated Neural Collaborative Filtering for privacy-preserving recommender systems

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Johannes Langelaar; Adam Strömme Mattsson; [2021]
    Keywords : Machine learning; Federated learning; Deep learning; Artificial intelligence; AI; Neural networks; Recommender systems; Recommendation systems; Collaborative filtering; Privacy; Federated averaging; Movielens;

    Abstract : In this thesis a number of models for recommender systems are explored, all using collaborative filtering to produce their recommendations. Extra focus is put on two models: Matrix Factorization, which is a linear model and Multi-Layer Perceptron, which is a non-linear model. READ MORE