zaky9

zaky9's Stars

• keras-team/keras

  Deep Learning for humans

  Language:Python62.8k1.9k12.4k19.6k

• ml-tooling/best-of-ml-python

  🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

  19.9k431572.7k

• deeppavlov/DeepPavlov

  An open source library for deep learning end-to-end dialog systems and chatbots.

  Language:Python6.8k2076431.2k

• maziarraissi/PINNs

  Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

  Language:Python4.5k122561.4k

• bnsreenu/python_for_microscopists

  https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

  Language:Jupyter Notebook4.2k116762.5k

• rasbt/python_reference

  Useful functions, tutorials, and other Python-related things

  Language:Jupyter Notebook3.8k23516931

• lululxvi/deepxde

  A library for scientific machine learning and physics-informed learning

  Language:Python3.1k59816807

• claimed-framework/component-library

  The goal of CLAIMED is to enable low-code/no-code rapid prototyping style programming to seamlessly CI/CD into production.

  Language:Jupyter Notebook2.3k89484k

• Paulescu/hands-on-rl

  Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻‍🦸🏽

  Language:Jupyter Notebook1.1k183139

• omniscientoctopus/Physics-Informed-Neural-Networks

  Investigating PINNs

  Language:Jupyter Notebook58176143

• rezaakb/pinns-torch

  PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.

  Language:Python46861673

• benmoseley/FBPINNs

  Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

  Language:Python375122976

• JohnWStockwellJr/SeisUnix

  The CWP/SU: Seismic Un*x Package - a free open seismic processing, research, and educational software package. Please seek distribution gzipped tar files at https://wiki.Seismic-Unix.org not the Github version.

  Language:AGS Script27651147126

• okada39/pinn_wave

  Physics Informed Neural Network (PINN) for the wave equation.

  Language:Python1585229

• QuakeMigrate/QuakeMigrate

  A Python package for automatic earthquake detection and location using waveform migration and stacking.

  Language:Python15186536

• lululxvi/hpinn

  hPINN: Physics-informed neural networks with hard constraints

  Language:Jupyter Notebook12751039

• viictorjs/Refrapy

  A Python 3 based program for seismic refraction data processing.

  Language:Python7972228

• soham2707/Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning

  This is a project on "Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning" using Pytorch, python, deep learning, gru, plotly

  Language:Jupyter Notebook66109

• yohanesnuwara/DASLab

  Distributed acoustic sensing lab developed @ RITE CO2 Storage Research Group

  Language:Jupyter Notebook572019

• pyrocko/lightguide

  Tools for distributed acoustic sensing data.

  Language:Python515612

• ASN-Norway/simpleDAS

  Python reader for ASN DAS files

  Language:Python19178

• hadi-tim/sdp-seismic-unix

  Seismic Data Processing using open source software Seismic Unix

  Language:Jupyter Notebook18133

• machinedecision/code_sample

  code_sample

  Language:Jupyter Notebook17104

• ManuelMBaumann/elastic_benchmarks

  Benchmark problems in 2D and 3D for the elastic wave equation.

  Language:Python14308

• DAS-RCN/continuous_data_handling

  Methods for handling continuous DAS data (loading, buffering, data processing...)

  Language:Jupyter Notebook13201

• izzatum/laplace-hypopinn

  Notebooks repository for "Laplace HypoPINN: Physics-Informed Neural Network for hypocenter localization and its predictive uncertainty"

  Language:Jupyter Notebook11102

• XuZitai/DNLR

  Language:Python921

• hatsyim/globenn

  Repository containing files pertaining to the A Neural Network Based Global Traveltime Function (GlobeNN) paper.

  Language:Jupyter Notebook8201

• norery/PCNN-SH2d

  The demo code for "Physics-enhanced neural networks for half-space seismic wave modeling"

  Language:Python6215

• zaky9/t81_558_deep_learning

  Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

  Language:Jupyter Notebook1100