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08/10/2023
GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks
The computation of the seismic wavefield by solving the Helmholtz equati...
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08/09/2023
Optimizing a Transformer-based network for a deep learning seismic processing workflow
StorSeismic is a recently introduced model based on the Transformer to a...
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07/16/2023
Joint Microseismic Event Detection and Location with a Detection Transformer
Microseismic event detection and location are two primary components in ...
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06/22/2023
A prior regularized full waveform inversion using generative diffusion models
Full waveform inversion (FWI) has the potential to provide high-resoluti...
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05/25/2023
PINNslope: seismic data interpolation and local slope estimation with physics informed neural networks
Interpolation of aliased seismic data constitutes a key step in a seismi...
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05/13/2023
Physics reliable frugal uncertainty analysis for full waveform inversion
Full waveform inversion (FWI) enables us to obtain high-resolution veloc...
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05/11/2023
LatentPINNs: Generative physics-informed neural networks via a latent representation learning
Physics-informed neural networks (PINNs) are promising to replace conven...
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04/09/2023
Microseismic source imaging using physics-informed neural networks with hard constraints
Microseismic source imaging plays a significant role in passive seismic ...
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02/26/2023
Efficient physics-informed neural networks using hash encoding
Physics-informed neural networks (PINNs) have attracted a lot of attenti...
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12/30/2022
Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion
Uncertainty quantification is crucial to inverse problems, as it could p...
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09/25/2022
Transfer learning for self-supervised, blind-spot seismic denoising
Noise in seismic data arises from numerous sources and is continually ev...
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05/28/2022
Laplace HypoPINN: Physics-Informed Neural Network for hypocenter localization and its predictive uncertainty
Several techniques have been proposed over the years for automatic hypoc...
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04/30/2022
StorSeismic: A new paradigm in deep learning for seismic processing
Machine learned tasks on seismic data are often trained sequentially and...
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09/29/2021
PINNup: Robust neural network wavefield solutions using frequency upscaling and neuron splitting
Solving for the frequency-domain scattered wavefield via physics-informe...
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09/15/2021
The potential of self-supervised networks for random noise suppression in seismic data
Noise suppression is an essential step in any seismic processing workflo...
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09/11/2021
MLReal: Bridging the gap between training on synthetic data and real data applications in machine learning
Among the biggest challenges we face in utilizing neural networks traine...
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08/17/2021
Direct domain adaptation through reciprocal linear transformations
We propose a direct domain adaptation (DDA) approach to enrich the train...
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02/08/2020
ML-misfit: Learning a robust misfit function for full-waveform inversion using machine learning
Most of the available advanced misfit functions for full waveform invers...
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02/08/2020