Sökning: "generativa modeller"

Visar resultat 11 - 15 av 59 uppsatser innehållade orden generativa modeller.

1. 11. Deep Generative Modeling : An Overview of Recent Advances in Likelihood-based Models and an Application to 3D Point Cloud Generation

   Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Shams Methnani; [2023]
   Nyckelord :;

   Sammanfattning : Deep generative modeling refers to the process of constructing a model, parameterized by a deep neural network, that learns the underlying patterns and structures of the data generating process which produced the samples in a given dataset, in order to generate novel samples that resemble those in the original dataset. Deep generative models for 3D shape generation hold significant importance to various fields including robotics, medical imaging, manufacturing, computer animation and more. LÄS MER

3. 12. Using a Deep Generative Model to Generate and Manipulate 3D Object Representation

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

   Författare :Yu Hu; [2023]
   Nyckelord :Neural networks; point cloud; 3D shape generation; 3D shape manipulation; classification; Neurala nätverk; punktmoln; generering av 3D-former; manipulation av 3Dformer; klassificering;

   Sammanfattning : The increasing importance of 3D data in various domains, such as computer vision, robotics, medical analysis, augmented reality, and virtual reality, has gained giant research interest in generating 3D data using deep generative models. The challenging problem is how to build generative models to synthesize diverse and realistic 3D objects representations, while having controllability for manipulating the shape attributes of 3D objects. LÄS MER

4. 13. Generating Extreme Value Distributions in Finance using Generative Adversarial Networks

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :William Nord-Nilsson; [2023]
   Nyckelord :Extreme Value Theory; Generative Adversarial Networks; Stress Testing; Machine Learning; Convolutional Neural Networks; evtGAN; Extreme Events; Extremvärdesteori; Generativa nätverk; Stresstestning; Maskininlärning; Djupt neuralt nätverk; evtGAN; Extrema händelser;

   Sammanfattning : This thesis aims to develop a new model for stress-testing financial portfolios using Extreme Value Theory (EVT) and General Adversarial Networks (GANs). The current practice of risk management relies on mathematical or historical models, such as Value-at-Risk and expected shortfall. LÄS MER

5. 14. Keeping tabs on GPT-SWE : Classifying toxic output from generative language models for Swedish text generation

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

   Författare :Isak Pettersson; [2022]
   Nyckelord :Active learning; Classification; Language models; Natural Language Processing; Swedish; Transformers; Toxic text; Aktiv inlärning; Klassificering; Språkmodeller; Språkteknologi; Svenska; Transformer nätverk; Toxisk text;

   Sammanfattning : Disclaimer: This paper contains content that can be perceived as offensive or upsetting. Considerable progress has been made in Artificial intelligence (AI) and Natural language processing (NLP) in the last years. LÄS MER

7. 15. An empirical comparison of generative capabilities of GAN vs VAE

   Kandidat-uppsats, KTH/Datavetenskap

   Författare :Norma Cristina Cueto Ceilis; Hanna Peters; [2022]
   Nyckelord :;

   Sammanfattning : Generative models are a family of machine learning algorithms that are aspire to enable computers to understand the real world. Their capability to understand the underlying distribution of data enables them to generate synthetic data from the data they are trained on. LÄS MER