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al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

astrophy_py_stacup_bdu_cutn_iucaa_2023

This repository hosts materials and code from the 'School on Statistical Techniques in Astrophysics & Cosmology Using Python (STACUP)' (Oct 16-20, 2023) at CUTN- BDU, Tiruchirapalli.  These resources are designed to support the attendees in exploring statistical techniques & their applications in astrophysics & cosmology using Python programming.

bidirectional-deep-readout-echo-state-network

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

dynamic-adaptation-network

echotorch

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

fortran_magic

An extension for IPython/Jupyter that helps to use Fortran in your interactive session.

hamiltonian-nn

Code for our paper "Hamiltonian Neural Networks"

harmonic-oscillator-pinn

Code accompanying my blog post: So, what is a physics-informed neural network?

hello-world

First repository built on GitHub

hybrid-reservoir-computing

simplified hybrid reservoir computing code

ipc

learning-unseen-attractors-paper-code

Code for the paper "Learning Unseen Coexisting Attractors"

marburg-phy-neuralnet-quantum-manybody

physics meets neural networks

matplotlib-cheatsheets

Official Matplotlib cheat sheets

nextgenrcbasins

ng-rc-paper-code

Code for the paper "Next Generation Reservoir Computing"

parallelized-reservoir-computing

This repository contains code for parallelized prediction of spatiotemporal chaotic data using reservoir computing as described in the paper: Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach (Physical Review Letters, 120, 024102 (2018)).

physical-reservoir-computing

A random recurrently connected mass-spring-damper network as a physical reservoir computing system

pinn-package

Physics-informed neural networks package

pycml

Python functions for Coupled Map Lattices

rasha-shanaz.github.io

reservoir

Code for Reservoir computing (Echo state network)

reservoir-computing

reservoir-computing-lyapunov-exponents

Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data. Chaos 27, 121102 (2017); https://doi.org/10.1063/1.5010300

reservoirpy

A simple and flexible code for Reservoir Computing architectures like Echo State Networks

rnn-rc-chaos

RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.

time-series-classification-and-clustering-with-reservoir-computing

Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

turbulence-modeling-piml

Data-driven Reynolds stress modeling with physics-informed machine learning

tusk

Refined Evernote desktop app