Essays about: "TensorFlow Probability"
Found 5 essays containing the words TensorFlow Probability.
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1. Evaluation of Probabilistic Programming Frameworks
University essay from Uppsala universitet/Statistiska institutionenAbstract : In recent years significant progress has been made in the area of Probabilistic Programming, contributing to a considerably easier workflow for quantitative research in many fields. However, as new Probabilistic Programming Frameworks (PPFs) are continuously being created and developed, there is a need for finding ways of evaluating and benchmarking these frameworks. READ MORE
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2. Deep Bayesian Neural Networks for Prediction of Insurance Premiums
University essay from KTH/Matematisk statistikAbstract : In this project, the problem concerns predicting insurance premiums and particularly vehicle insurance premiums. These predictions were made with the help of Bayesian Neural Networks (BNNs), a type of Artificial Neural Network (ANN). The central concept of BNNs is that the parameters of the network follow distributions, which is beneficial. READ MORE
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3. Deep Learning for Positioning with MUSIC
University essay from Linköpings universitet/KommunikationssystemAbstract : Estimating an object’s position can be of great interest in several applications,and there exists many different methods to do so. One approach is with Directionof Arrival (DOA) measurements from receivers to use the triangulation techniqueto estimate one or more transmitter’s position. READ MORE
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4. Ghosts of Our Past: Neutrino Direction Reconstruction Using Deep Neural Networks
University essay from Uppsala universitet/HögenergifysikAbstract : Neutrinos are the perfect cosmic messengers when it comes to investigating the most violent and mysterious astronomical and cosmological events in the Universe. The interaction probability of neutrinos is small, and the flux of high-energy neutrinos decreases quickly with increasing energy. READ MORE
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5. Deep Bayesian Neural Networks for Prediction of Insurance Premiums
University essay from KTH/Matematisk statistikAbstract : In this project, the problem concerns predicting insurance premiums and particularly vehicle insurance premiums. These predictions were made with the help of Bayesian Neural Networks (BNNs), a type of Artificial Neural Network (ANN). The central concept of BNNs is that the parameters of the network follow distributions, which is beneficial. READ MORE