Essays about: "deep Gaussian processes"
Found 5 essays containing the words deep Gaussian processes.
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1. Implementation of thermomechanical laser welding simulation : Predicting displacements of fusing A AISI304 T-JOINT
University essay from Högskolan i Skövde/Institutionen för ingenjörsvetenskapAbstract : Laser welding is an advanced joining technique with the capability to form deep, narrow, and precise welds. Numerical models are used to simulate the process in attempts of predicting distortions and stresses in the material. This is done to reduce physical testing, optimize processes and enable integrated product- and process development. READ MORE
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2. Gaussian Process Methods for Estimating Radio Channel Characteristics
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Gaussian processes (GPs) as a Bayesian regressionmethod have been around for some time. Since proven advant-ageous for sparse and noisy data, we explore the potential ofGaussian process regression (GPR) as a tool for estimating radiochannel characteristics. READ MORE
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3. Statistical Modeling of Separator Processes - An Application of Gaussian Processes with Bayesian Optimization
University essay from Lunds universitet/Matematisk statistikAbstract : The separator is a machine with many applications, commonly used to separate liquids or solids into components with different density. Each application demands its own unique set of process parameters to achieve optimal results. Often the procedure of finding the best process parameters is conducted empirically, which can be very time consuming. READ MORE
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4. Human Age Prediction Based on Real and Simulated RR Intervals using Temporal Convolutional Neural Networks and Gaussian Processes
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : Electrocardiography (ECG) is a non-invasive method used in medicine to track the electrical pulses sent by the heart. The time between two subsequent electrical impulses and hence the heartbeat of a subject, is referred to as an RR interval. READ MORE
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5. A Comparative Study of Black-box Optimization Algorithms for Tuning of Hyper-parameters in Deep Neural Networks
University essay from Luleå tekniska universitet/Institutionen för teknikvetenskap och matematikAbstract : Deep neural networks (DNNs) have successfully been applied across various data intensive applications ranging from computer vision, language modeling, bioinformatics and search engines. Hyper-parameters of a DNN are defined as parameters that remain fixed during model training and heavily influence the DNN performance. READ MORE