rfarell

2022_Tanaka_HamiltonianGP_NoisySparseData

This repository implements the 2022 paper 'Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data' by Tanaka et al.

adomvi

Automated Detection of Military Vehicles from Video Input

awesome-neural-ode

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

marker

Convert PDF to markdown quickly with high accuracy

deeponet-fno

DeepONet & FNO (with practical extensions)

ufno

U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow

PDEBench

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Bard-API

The unofficial python package that returns response of Google Bard through cookie value.

sbi-lecture-mit

Notebook to go along with a lecture for the MIT course 8.16: Data Science in Physics on neural simulation-based inference.

ml-physics-notebooks

Machine Learning for Physics and Astronomy Learning Check-ins

Physics-Informed-Neural-Networks-PINN-

In these notebooks we will see how we can use physics laws and small amounts of data to solve partial differential equation such as Poisson, Burger, and others using Neural Network. The first part pytorch was used but this built on Tensorflow.

NeuralSolvers

Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.

PINN

Simple PyTorch Implementation of Physics Informed Neural Network (PINN)

mojo

The Mojo Programming Language

idrlnet

IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.

deepgeostat

Code for the paper - "Bayesian deep learning for spatial interpolation in the presence of auxiliary information"

neuraloperator

Learning in infinite dimension with neural operators.

pinn_ode_tutorial

neurodiffeq

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

deepxde

A library for scientific machine learning and physics-informed learning

pydens

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

ImprovedDeepONets

PINNs

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

sciann-applications

A place to share problems solved with SciANN

2d-fluid-simulator

2D incompressible fluid solver implemented in Taichi.

langchain

🦜🔗 Build context-aware reasoning applications

uBlock

uBlock Origin - An efficient blocker for Chromium and Firefox. Fast and lean.

libg-fzf

Library Genesis TUI using fzf

donut

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

docquery

An easy way to extract information from documents