Essays about: "Generativa modeller"
Showing result 6 - 10 of 57 essays containing the words Generativa modeller.
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6. Evaluating Membership Inference Attacks on Synthetic Data Generated With Formal Privacy Guarantees
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Synthetic data generation using generative machine learning has been increasinglypublicized as a new tool for data anonymization. It promises to offer privacy whilemaintaining the statistical properties of the original dataset. This study focuses on the riskswith synthetic data by looking mainly at two aspects: privacy and utility. READ MORE
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7. Explainability to enhance creativity : A human-centered approach to prompt engineering and task allocation in text-to-image models for design purposes
University essay from Luleå tekniska universitet/Institutionen för ekonomi, teknik, konst och samhälleAbstract : As the power, utility, and prevalence of generative AI technologies continue to grow, the debate on whether and how designers should incorporate text-image models into the design process is gaining momentum. To ensure productivity, creativity, and human values, this project seeks to address design interaction and task allocation between designers, and generative AI models become essential. READ MORE
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8. A study about Active Semi-Supervised Learning for Generative Models
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : In many relevant scenarios, there is an imbalance between abundant unlabeled data and scarce labeled data to train predictive models. Semi-Supervised Learning and Active Learning are two distinct approaches to deal with this issue. READ MORE
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9. 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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10. Using a Deep Generative Model to Generate and Manipulate 3D Object Representation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE
