Found 171 datasets matching "Deep learning".
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This is a test collection for passage and document retrieval, produced in the TREC 2023 Deep Learning track. The Deep Learning Track studies information retrieval in a large training data regime....
Search relevance: 185.68 | Views last month: 4 -
The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes,...
Search relevance: 184.72 | Views last month: 2 -
Streamflow data (Fig. 1a) from the Global Streamflow Indices and Metadata Archive (GSIM) were compiled from repositories at https://doi.org/10.1594/PANGAEA.887477 and...
Search relevance: 178.76 | Views last month: 4 -
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...
Search relevance: 172.49 | Views last month: 26 -
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 159.53 | Views last month: 1 -
Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep learning models and deep...
Search relevance: 154.91 | Views last month: 2 -
This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for the analysis, Experiment A,...
Search relevance: 154.90 | Views last month: 0 -
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data...
Search relevance: 153.90 | Views last month: 2 -
This project aims to create a comprehensive framework for generating radio frequency (RF) datasets, designing deep learning (DL) detectors, and evaluating their detection performance using both...
Search relevance: 152.18 | Views last month: 0 -
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 151.26 | Views last month: 1 -
Process-guided deep learning water temperature predictions: 5a Lake Mendota detailed prediction data
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models...
Search relevance: 151.19 | Views last month: 0 -
This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture on generalizability when...
Search relevance: 151.02 | Views last month: 0 -
There are 3 child zip files included in this data release. 01_Codebase.zip contains a codebase for using deep learning to filter images based on the probability of any bird occurrence. It...
Search relevance: 151.00 | Views last month: 1 -
This model archive provides all data, code, and modeling results used in Barclay and others (2023) to assess the ability of process-guided deep learning stream temperature models to accurately...
Search relevance: 150.08 | Views last month: 1 -
This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other...
Search relevance: 148.67 | Views last month: 0 -
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were configured and...
Search relevance: 148.47 | Views last month: 0 -
This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other...
Search relevance: 147.02 | Views last month: 0 -
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB) models were configured and...
Search relevance: 144.23 | Views last month: 0 -
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: 143.86 | Views last month: 5 -
This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two...
Search relevance: 142.91 | Views last month: 0
