Found 75 datasets matching "neural networks".
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This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide...
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This dataset contains the spatiotemporal data used to train the spatiotemporal deep neural networks described in "Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal...
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This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide...
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Data describe the effects of metal oxide nanoparticles on total spikes and active electrodes after exposure to various concentrations for 1, 24 and 48 hrs, or after treatment with bicuculline....
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Background Classification of the electrocardiogram using Neural Networks has become a widely used method in recent years. The efficiency of these classifiers depends upon a number of...
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The GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) IFloodS dataset is a subset from the...
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The GPM Ground Validation Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) IFloodS dataset is a subset from the...
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Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machine learning...
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Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machine learning...
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This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a...
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This page contains 15 estimated quantiles for 9,203 level-12 Hydrologic Unit Code in the Southeastern United States for the decades 1950-1959, 1960-1969, 1970-1979, 1980-1989, 1990-1999, and...
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The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design...
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This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting...
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The BUTTER-E - Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER - Empirical Deep...
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Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in...
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This dataset contains the files, scripts and data that were used to run the simulations and data analyses for the manuscript. This dataset is associated with the following publication: Ball, K.,...
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PERSIANN Precipitation Climate Data Record (PERSIANN-CDR) is a daily quasi-global precipitation product for the period of 1982 to the present (note that there is a delay in data availability due...
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Learning and building GMDH polynomial neural networks and printing them as 3rd degree polynomial equation.
Search relevance: 67.15 | Views last month: 1 -
The Delaware River Basin (DRB) covers portions of five states (Delaware, Maryland, New Jersey, New York, and Pennsylvania) and several geologic provinces, encompassing much of the complex geology...
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The Deep Learning track focuses on IR tasks where a large training set is available, allowing us to compare a variety of retrieval approaches including deep neural networks and strong non-neural...
Search relevance: 66.30 | Views last month: 5
