Essays about: "Applications of computer in statistics"
Showing result 1 - 5 of 22 essays containing the words Applications of computer in statistics.
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1. Reinforcement Learning for the Optimization of Explicit Runge-Kutta Method Parameters
University essay from Lunds universitet/Matematik LTH; Lunds universitet/Matematik (naturvetenskapliga fakulteten); Lunds universitet/MatematikcentrumAbstract : Reinforcement learning is one of the three main paradigms in machine learning, which is increasingly used as a method to approach scientific problems. In this thesis, we introduce and use reinforcement learning to find the optimal parameters of a numerical solver. READ MORE
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2. Individual Layer Scaling and Redundancy Reduction of Singleshot Multiplane Images for View Synthesis
University essay from Lunds universitet/Matematik LTHAbstract : Image-based rendering for view synthesis is a field within computer vision that has seen a growing number of research activity within the past few years, much due to deep learning techniques emerging, allowing researchers to re-format view synthesis as a learning problem. The multiplane image (MPI) is a recently proposed learning-based layered 3D representation, created from one or a few input images for the purpose of rendering novel views. READ MORE
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3. Generating Geospatial Trip DataUsing Deep Neural Networks
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : Synthetic data provides a good alternative to real data when the latter is not sufficientor limited by privacy requirements. In spatio-temporal applications, generating syntheticdata is generally more complex due to the existence of both spatial and temporal dependencies. READ MORE
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4. Road Segmentation and Optimal Route Prediction using Deep Neural Networks and Graphs
University essay from KTH/Matematik (Avd.)Abstract : Observing the earth from above is a great way of understanding our world better. From space, many complex patterns and relationships on the ground can be identified through high-quality satellite data. READ MORE
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5. Time Series Active Learning using Automated Feature Extraction
University essay from Lunds universitet/Matematisk statistikAbstract : Time series classification is a prevalent problem for sensor data in an industrial setting. The ability to classify time series correctly allows for predictive maintenance which is the process of optimally maintaining assets and ensuring minimal ”down-time” of machines or processes. READ MORE
