Search results for learning models
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189 datasets for “learning models”
- Data.gov Catalog
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography
Oak Ridge National LaboratoryUpdated 17 Feb 2025
This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper …
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- Data.gov Catalog
GeoCryoAI: Ensemble Learning and the Permafrost Carbon Feedback in Alaska, 1963-2022
ORNL_DAACUpdated 5 Nov 2026
… an artificial intelligence-driven model, GeoCryoAI. GeoCryoAI is a hybridized process-constrained ensemble learning framework consisting of stacked …
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- Open Government Canada
CCDR: Volume 46-6 -June 2020: Artificial intelligence in public health
Public Health Agency of Canada | Agence de la santé publique du CanadaUpdated 5 Jun 2020
The Canada Communicable Disease Report is a bilingual, open-access, peer-reviewed journal on the prevention and control …
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- Data.gov Catalog
Classification
DashlinkUpdated 31 Mar 2025
… A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each …
- Data.gov Catalog
Utah FORGE 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress - Final Report
University of PittsburghUpdated 22 Dec 2025
… The physics-based model accounts for thermo-poro-mechanical effects induced by drilling, fluid circulation, and logging operations …
- Open Government Canada
Briefing material for the President of the Public Health Agency of Canada’s appearance at the Standing Committee on Health (HESA) of May 2, 2022
Public Health Agency of Canada | Agence de la santé publique du CanadaUpdated 20 Nov 2024
Briefing material for the President of the Public Health Agency of Canada’s appearance at the Standing Committee …
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 16 Oct 2025
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Jan 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 2 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 7 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 25 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 20 Apr 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Geoscience Australia DataUpdated 30 Apr 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 11 Jan 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 23 Jan 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 12 Feb 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 5 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 16 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
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- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 29 Mar 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
- HTML
- data.gov.au
Predicting Seabed Sand Content across the Australian Margin Using Machine Learning and Geostatistical Methods
Australian Ocean Data NetworkUpdated 4 Apr 2026
… The predictive accuracy changes with methods, input secondary variables, model averaging, search window size and the study region …
- HTML