Essays about: "Generativa modeller"
Showing result 16 - 20 of 57 essays containing the words Generativa modeller.
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16. Generating synthetic golf courses with deep learning : Investigation into the uses and limitations of generative deep learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The power of generative deep learning has increased very quickly in the past ten years and modern models are now able to generate human faces that are indistinguishable from real ones. This thesis project will investigate the uses and limitations of this technology by attempting to generate very specific data, images of golf holes. READ MORE
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17. Attribute Embedding for Variational Auto-Encoders : Regularization derived from triplet loss
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Techniques for imposing a structure on the latent space of neural networks have seen much development in recent years. Clustering techniques used for classification have been used to great success, and with this work we hope to bridge the gap between contrastive losses and Generative models. READ MORE
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18. Analyzing the Negative Log-Likelihood Loss in Generative Modeling
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE
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19. Basil-GAN
University essay from KTH/Matematisk statistikAbstract : Developments in computer vision has sought to design deep neural networks which trained on a large set of images are able to generate high quality artificial images which share semantic qualities with the original image set. A pivotal shift was made with the introduction of the generative adversarial network (GAN) by Goodfellow et al.. READ MORE
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20. Evaluation of generative machine learning models : Judging the quality of generated data with the use of neural networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Generative machine learning models are capable of generating remarkably realistic samples. Some models generate images that look entirely natural, and others generate text that reads as if a human wrote it. However, judging the quality of these models is a major challenge. READ MORE
