10 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Semi-Supervised Segmentation of Salt Bodies in Seismic Images using an Ensemble of Convolutional Neural Networks

ybabakhin/kaggle_salt_bes_phalanx 9 Apr 2019

Seismic image analysis plays a crucial role in a wide range of industrial applications and has been receiving significant attention.

OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion

lanl/openfwi 4 Nov 2021

The recent success of data-driven FWI methods results in a rapidly increasing demand for open datasets to serve the geophysics community.

70 years of machine learning in geoscience in review

JesperDramsch/70-Years-of-Machine-Learning-in-Geoscience-in-Review 16 Jun 2020

I explore the shift of kriging towards a mainstream machine learning method and the historic application of neural networks in geoscience, following the general trend of machine learning enthusiasm through the decades.

A General Framework Combining Generative Adversarial Networks and Mixture Density Networks for Inverse Modeling in Microstructural Materials Design

zyz293/GAN-MDN 26 Jan 2021

Microstructural materials design is one of the most important applications of inverse modeling in materials science.

Direct Velocity Inversion of Ground Penetrating Radar Data Using GPRNet

zxleong/GPRNet Journal of Geophysical Research: Solid Earth 2021

We simulate numerous GPR data from a range of pseudo‐random velocity models and feed the datasets into GPRNet for training.

Data-driven modeling of time-domain induced polarization

clberube/ip-vae 30 Jul 2021

We present a novel approach for data-driven modeling of the time-domain induced polarization (IP) phenomenon using variational autoencoders (VAE).

Viskositas: Viscosity Prediction of Multicomponent Chemical Systems

patrick21081995/VISKOSITAS 2 Aug 2022

Viscosity in the metallurgical and glass industry plays a fundamental role in its production processes, also in the area of geophysics.

Learned multiphysics inversion with differentiable programming and machine learning

slimgroup/jutuldarcyrules.jl 12 Apr 2023

We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e. g., seismic and medical ultrasound), regularization with learned priors, and learned neural surrogates for multiphase flow simulations.

LSTM-Based Forecasting Model for GRACE Accelerometer Data

darbeheshti/lstm-based-analysis-for-grace-accelerometers 16 Aug 2023

The Gravity Recovery and Climate Experiment (GRACE) satellite mission, spanning from 2002 to 2017, has provided a valuable dataset for monitoring variations in Earth's gravity field, enabling diverse applications in geophysics and hydrology.

Rethinking materials simulations: Blending direct numerical simulations with neural operators

vivek-brown/UNet-with-temporal-conditioning 8 Dec 2023

This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism that enables accurate extrapolation and efficient time-to-solution predictions of the dynamics.