Sökning: "Generative Modeling"

Visar resultat 1 - 5 av 28 uppsatser innehållade orden Generative Modeling.

1. 1. Visualization and analysis of object states using diffusion models and PyTorch

   Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

   Författare :Christopher Nyberg; [2024]
   Nyckelord :;

   Sammanfattning : Artificial Intelligence (AI) is an extremely rapidly growing field in modern technology. As the applications of AI expand, the ability to accurately analyze and predict the condition of various objects through various models has profound implications across numerous industries. LÄS MER

3. 2. Predicting the Unpredictable – Using Language Models to Assess Literary Quality

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Yaru Wu; [2023]
   Nyckelord :perplexity; variance; unpredictability; homogeneity; generative pre-trained models; text generation; literary quality;

   Sammanfattning : People read for various purposes like learning specific skills, acquiring foreign languages, and enjoying the pure reading experience, etc. This kind of pure enjoyment may credit to many aspects, such as the aesthetics of languages, the beauty of rhyme, and the entertainment of being surprised by what will happen next, the last of which is typically featured in fictional narratives and is also the main topic of this project. LÄS MER

4. 3. Possibilities and Challenges of City Planning using 3D Visualization : A systematic literature review on the possibilities of city visualization using 3D computer graphics and the utility of parametric design

   Kandidat-uppsats, Blekinge Tekniska Högskola

   Författare :Benjamin Lind Nilsson; [2023]
   Nyckelord :;

   Sammanfattning : There exist numerous previously conducted surveys, studies and written articles on the topic of 3D geo-visualization. The subject has been pursued increasingly for the last two decades. In the late 1960s, digital earth, the idea of a digital copy of the real world was first proposed. However, hardware capabilities were limited. LÄS MER

5. 4. 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

7. 5. Scenario Generation for Stress Testing Using Generative Adversarial Networks : Deep Learning Approach to Generate Extreme but Plausible Scenarios

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Jonas Gustafsson; Conrad Jonsson; [2023]
   Nyckelord :Machine Learning; Generative Adversarial Network GAN ; Wasserstein Generative Adversarial Network WGAN ; Scenario Generation; Stress Testing; Central Counterparty Clearing;

   Sammanfattning : Central Clearing Counterparties play a crucial role in financial markets, requiring robust risk management practices to ensure operational stability. A growing emphasis on risk analysis and stress testing from regulators has led to the need for sophisticated tools that can model extreme but plausible market scenarios. LÄS MER