Essays about: "Generativ modell"

Showing result 1 - 5 of 31 essays containing the words Generativ modell.

  1. 1. Utilizing GPT for Interactive Dialogue-based Learning Scenarios : A Comparative Analysis with Rasa

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Valdimar Björnsson; [2023]
    Keywords : Generative Pretrained Transformer; Rasa; Interactive Tutoring Systems; Conversational AI; Education Technology; Generativ förtränad transformator; Rasa; interaktiva handledningssystem; Conversational AI; Education Technology;

    Abstract : This thesis explores the use of advanced language models, specifically OpenAI’s Generative Pretrained Transformer (GPT), in the context of interactive tutoring systems built within a Unity-based game environment. The central problem addressed is whether the recent advancements in large language models make them feasible and useful to function as tutors specifically in providing meaningful, engaging, and educationally rich user interactions on a dialogue based learning platform developed by Fictive Reality. READ MORE

  2. 2. Highway Traffic Forecasting with the Diffusion Model : An Image-Generation Based Approach

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Pengnan Chi; [2023]
    Keywords : Diffusion model; Traffic forecasting; Generative model; Image processing; Spatial temporal modelling; Diffusionsmodell; Trafikprognos; Generativ modell; Bildbehandling; Rumsligtemporal modellering;

    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

  3. 3. 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 statistik

    Author : Shams Methnani; [2023]
    Keywords : ;

    Abstract : 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

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

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

    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

  5. 5. Towards topology-aware Variational Auto-Encoders : from InvMap-VAE to Witness Simplicial VAE

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Aniss Aiman Medbouhi; [2022]
    Keywords : Variational Auto-Encoder; Nonlinear dimensionality reduction; Generative model; Inverse projection; Computational topology; Algorithmic topology; Topological Data Analysis; Data visualisation; Unsupervised representation learning; Topological machine learning; Betti number; Simplicial complex; Witness complex; Simplicial map; Simplicial regularization.; Variations autokodare; Ickelinjär dimensionalitetsreducering; Generativ modell; Invers projektion; Beräkningstopologi; Algoritmisk topologi; Topologisk Data Analys; Datavisualisering; Oövervakat representationsinlärning; Topologisk maskininlärning; Betti-nummer; Simplicielt komplex; Vittneskomplex; Simpliciel avbildning; Simpliciel regularisering.;

    Abstract : Variational Auto-Encoders (VAEs) are one of the most famous deep generative models. After showing that standard VAEs may not preserve the topology, that is the shape of the data, between the input and the latent space, we tried to modify them so that the topology is preserved. READ MORE