Essays about: "Bayesian Neural Network"
Showing result 1 - 5 of 69 essays containing the words Bayesian Neural Network.
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1. Parameter Inference for Stochastic Models of Gene Expression in Eukaryotic Cells
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Simulation models are often used to study a system or phenomenon. However, before a simulation model can be used, its parameter needs to be fit to mimic observed data. This is called the parameter inference problem. READ MORE
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2. Modelling Long Term Memory in the Bayesian Confidence Neural Network Model
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Memory is a fascinating and complex part of human life. Understanding memory and simulating itthrough modelling can help society take steps towards understanding health issues such asAlzheimer's, dementia and amnesia. READ MORE
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3. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction
University essay from KTH/Matematisk statistikAbstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE
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4. A Bayesian Bee Colony Algorithm for Hyperparameter Tuning of Stochastic SNNs : A design, development, and proposal of a stochastic spiking neural network and associated tuner
University essay from Uppsala universitet/Signaler och systemAbstract : With the world experiencing a rapid increase in the number of cloud devices, continuing to ensure high-quality connections requires a reimagining of cloud. One proponent, edge computing, consists of many distributed and close-to-consumer edge servers that are hired by the service providers. READ MORE
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5. Forecasting CO2 Emissions in Sweden with a Bayesian Neural Network
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Carbon dioxide (CO2) is the main constituent of greenhouse gases whose increasing concentrations creates a multitude of different environmental problems. Developing an effective predictive modell for forecasting CO2 is therefore of great importance for future policymakers. READ MORE