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Create synthetic seismic volumes with various labelled river channels.
According to Building realistic structure models to train convolutional neural networks for seismic structural interpretation
Three-Dimensional Implicit Structural Modeling Using Convolutional Neural Network
Latent-compression-free generative diffusion for implicit structural modeling with geological priors and geophysical regularization.
How to convert segy file to numpy format.
A library for scientific machine learning and physics-informed learning
StorSeismic: An approach to pre-train a neural network to store seismic data features
Seismic Foundation Model
The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)
Code and hyperparameters for the paper "Generative Adversarial Networks"
Official reproducible material for Noise attenuation in distributed acoustic sensing data using a guided unsupervised deep learning network
PyTorch Implementation of "Resource Efficient 3D Convolutional Neural Networks", codes and pretrained models.
An unsupervised learning framework for 2D/3D seismic random noise attenuation
The LOdasdenoising package stores the reproducible and open-access scripts for protecting the weak signals in distributed acoustic sensing data processing using local orthogonalization (LO).
Data used to generate the figures and support the findings of manuscript entitled, "Photonic seismology in Monterey Bay: Dark fiber1DAS illuminates offshore faults and coastal ocean" by Nathaniel J…
Wave-equation based inversion with amortized variational Bayesian inference
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习