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ISSN: 2666-5441

The potential of self-supervised networks for random noise suppression in seismic data

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Local earthquakes detection: A benchmark dataset of 3-component seismograms built on a global scale

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Wavefield solutions from machine learned functions constrained by the Helmholtz equation

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Exact Conditioning of Regression Random Forest for Spatial Prediction

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Rapid identification of high-quality marine shale gas reservoirs based on the oversampling method and random forest algorithm

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Machine learning-based prediction of trace element concentrations using data from the Karoo large igneous province and its application in prospectivity mapping

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Automatic fault instance segmentation based on mask propagation neural network

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The benefits and dangers of using artificial intelligence in petrophysics

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Seismic labeled data expansion using variational autoencoders

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Site suitability for Aromatic Rice cultivation by integrating Geo-spatial and Machine learning algorithms in Kaliyaganj C.D. block, India

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ShakeDaDO: A data collection combining earthquake building damage and ShakeMap parameters for Italy

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Towards a fully data-driven prospectivity mapping methodology: A case study of the Southeastern Churchill Province, Québec and Labrador

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Classification random forest with exact conditioning for spatial prediction of categorical variables

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Capsule network-based approach for estimating grassland coverage using time series data from enhanced vegetation index

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A convolutional recurrent neural network for strong convective rainfall nowcasting using weather radar data in Southeastern Brazil

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Ensemble hybrid machine learning methods for gully erosion susceptibility mapping: K-fold cross validation approach

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Microleveling aerogeophysical data using deep convolutional network and MoG-RPCA

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Flood susceptibility assessment using artificial neural networks in Indonesia

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Application of neural network to speed-up equilibrium calculations in compositional reservoir simulation

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Advanced geochemical exploration knowledge using machine learning: Prediction of unknown elemental concentrations and operational prioritization of Re-analysis campaigns

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Random forest for spatial prediction of censored response variables

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A study on small magnitude seismic phase identification using 1D deep residual neural network

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Sparse inversion-based seismic random noise attenuation via self-paced learning

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