Essays about: "generativ modellering"
Showing result 1 - 5 of 11 essays containing the words generativ modellering.
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1. Highway Traffic Forecasting with the Diffusion Model : An Image-Generation Based Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Forecasting of highway traffic is a common practice for real traffic information system, and is of vital importance to traffic management and control on highways. As a typical time-series forecasting task, we want to propose a deep learning model to map the historical sensory traffic values (e.g., speed, flow) to future traffic forecasts. READ MORE
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2. Deep Generative Modeling : An Overview of Recent Advances in Likelihood-based Models and an Application to 3D Point Cloud Generation
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : 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. READ MORE
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3. 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
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4. Synthetic Data Generation for the Financial Industry Using Generative Adversarial Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Following the introduction of new laws and regulations to ensure data protection in GDPR and PIPEDA, interests in technologies to protect data privacy have increased. A promising research trajectory in this area is found in Generative Adversarial Networks (GAN), an architecture trained to produce data that reflects the statistical properties of its underlying dataset without compromising the integrity of the data subjects. READ MORE
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5. Particle Filter Bridge Interpolation in GANs
University essay from KTH/Matematisk statistikAbstract : Generative adversarial networks (GANs), a type of generative modeling framework, has received much attention in the past few years since they were discovered for their capacity to recover complex high-dimensional data distributions. These provide a compressed representation of the data where all but the essential features of a sample is extracted, subsequently inducing a similarity measure on the space of data. READ MORE
