Essays about: "Bayesian parameter estimation"
Showing result 1 - 5 of 23 essays containing the words Bayesian parameter estimation.
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1. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
University essay from Lunds universitet/Statistiska institutionenAbstract : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. READ MORE
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2. Bayesian inference methods for parameter estimation : Implementation and benchmarking
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : In this study, three implementations of the nested sampling algorithm have been implemented, in the programming language Rust, compared and benchmarked. These variations consist of a classic version, closely resembling the first appearance of the algorithm, a version that produces samples from a single ellipsoid, and a version tha tuses multiple ellipsoids to generate its samples. READ MORE
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3. Simultaneous Bayesian parameter estimation and particle-tracking including calculation of mis-linking probabilities
University essay from Lunds universitet/Institutionen för astronomi och teoretisk fysik - Genomgår omorganisationAbstract : Since 1994 super-resolution microscopes enable us to visualize processes in the nanome- ter regime where bio-molecules work. Consequently, there is a great need for methods analyzing the generated data to transfer the motion of molecules, seen as white dots, into trajectories. READ MORE
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4. Fantastic spiking neural networks and how to train them
University essay fromAbstract : Spiking neural networks are a new generation of neural networks that use neuronal models that are more biologically plausible than the typically used perceptron model. They do not use analog values to perform computations, as is the case in regular neural networks, but rely on spatio-temporal information encoded into sequences of delta-functions known as spike trains. READ MORE
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5. Modelling the adoption of SPACs with Bass’ diffusion model
University essay from Mälardalens högskola/Akademin för utbildning, kultur och kommunikationAbstract : The recent observed growth in the diffusion of Special Purpose Acquisition Companies phenomena on the U.S stock market may be analyzed from a mathematical standpoint, where different approaches of the Bass Diffusion Model might be utilized. READ MORE
