HediChen

HediChen's Stars

• HangGaoNUDT/HazardousWindDetection

  Language:Jupyter Notebook1

• reecehuff/StrainNet

  StrainNet is a deep neural network for measuring deformation from images

  Language:Python3

• ColinLii/CC-FJpy

  A Python Package for seismic ambient noise cross-correlation and the frequency-Bessel transform method

  Language:C++12252

• ShaoboYang-USTC/EGFAnalysisPy

  基于图像分析方法，从经验格林函数或互相关函数中计算面波群速度及相速度频散能量图，进而使用基于人工智能的频散曲线提取方法DisperPicker从频散能量图中自动提取频散曲线。

  Language:Python205

• jxensing/ftanpy

  Frequency-Time ANalysis (FTAN) in python

  Language:Python102

• ShaoboYang-USTC/DisperPicker

  Automatically extracting dispersion curves via deep learning

  Language:Python299

• martijnende/jDAS

  Coherence-based Deep Learning denoising of DAS data

  Language:Python243

• noisepy/NoisePy

  Ambient-Noise Seismology Package

  Language:Python16174

• WenjieDu/PyPOTS

  A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

  Language:Python94189

• Guillem96/madgan-pytorch

  Multivariate Anomaly Detection with GAN (MAD-GAN) PyTorch modern implementation.

  Language:Python262

• LiDan456/MAD-GANs

  Applied generative adversarial networks (GANs) to do anomaly detection for time series data

  Language:Python510158

• ashiq24/UNO

  Language:Jupyter Notebook468

• DedalusProject/dedalus

  A flexible framework for solving PDEs with modern spectral methods.

  Language:Python486114

• katiana22/latent-deeponet

  Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."

  Language:Python4110

• KTH-FlowAI/Identifying-regions-of-importance-in-wall-bounded-turbulence-through-explainable-deep-learning

  Code for reproducing the article: Identifying regions of importance in wall-bounded turbulence through explainable deep learning.

  Language:Python41

• Ali-Stanford/PointNetCFD

  Point-cloud deep learning for prediction of fluid flow fields on irregular geometries (supervised learning)

  Language:Jupyter Notebook218

• lululxvi/deepxde

  A library for scientific machine learning and physics-informed learning

  Language:Python2.6k728

• lululxvi/tutorials

  Tutorials on deep learning, Python, and dissipative particle dynamics

  Language:Jupyter Notebook14952

• sciann/sciann

  Deep learning for Engineers - Physics Informed Deep Learning

  Language:Python316113

• sciann/sciann-applications

  A place to share problems solved with SciANN

  Language:Jupyter Notebook236127

• raj-brown/APMA_2070_ENGN_2912_SPRING_2024

  Language:Jupyter Notebook3711

• lululxvi/deeponet

  Learning nonlinear operators via DeepONet

  Language:Python494137

• neuraloperator/Geo-FNO

  Geometry-Aware Fourier Neural Operator (Geo-FNO)

  Language:Jupyter Notebook16345

• neuraloperator/physics_informed

  Language:Python34182

• neuraloperator/graph-pde

  Using graph network to solve PDEs

  Language:Python32382

• neuraloperator/neuraloperator

  Learning in infinite dimension with neural operators.

  Language:Python2k528

• LiuYangMage/in-context-operator-networks

  ICON for in-context operator learning

  Language:Python357

• idrl-lab/PINNpapers

  Must-read Papers on Physics-Informed Neural Networks.

  Language:Python826146

• gstinoco/Cloud-Generation

  Generate regular or irregular clouds of points from contours or meshes.

  Language:Python1

• gstinoco/mGFD

  Meshless Generalized Finite Differences for numerically solve Partial Differential Equations

  Language:Python1