mq-jonathan-xu Goto Github PK

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

peakfit

A peak-fitting tool based on MATLAB for spectroscopic data analysis.

phase-space-sampling

Reduce a large and high-dimensional dataset by downselecting data uniformly in phase space

physics-based-deep-learning

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

physics-informed-ml-study

study code for physics informed machine learning and deep learning

pilegrouptool

An Application for Understanding Behaviour of Laterally Loaded Piles

pinns

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

plugin-gui

Software for processing, recording, and visualizing multichannel electrophysiology data

pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

py_analysis

Finite-difference and finite-element implementation of the py method to analyze laterally loaded pile foundations

pybladed

Wrapper around Bladed API and access to binary result files.

pydatview

A crossplatform GUI to plot tabulated data from files (e.g. CSV, Excel, OpenFAST, HAWC2, Flex...), or python pandas dataframes

pykalman

Kalman Filter, Smoother, and EM Algorithm for Python

pymbc3

MBC3 in Python

pyoma

pyoptsparse

pyOptSparse is an object-oriented framework for formulating and solving nonlinear constrained optimization problems in an efficient, reusable, and portable manner.

python

Python code for Bayesian Conditional Cointegration

r-test

rcnn

R-CNN: Regions with Convolutional Neural Network Features

rddc2020

road damage detection challenge 2020

road-damage-detection

Keeping roads in a good condition is vital to safe driving. To monitor the degradation of road conditions is one of the important component in transportation maintenance which is labor intensive and requires domain expertise. Automatic detection of road damage is an important task in transportation maintenance for driving safety assurance. The intensity of damage and complexity of the background, makes this process a challenging task. A deep-learning based methodology for damage detection is proposed in this project after being inspired by recent success on applying Deep- learning in Computer Sciences. A dataset of 9,053 images is taken with the help of a low cost smart phone and a quantitative evaluation is conducted, which in turn demonstrates that the superior damage detection performance using deep-learning methods perform extremely well when compared with features extracted with existing hand-craft methods. Using convolutional neural networks to train the damage detection model with our dataset, we use the state-of-the-art object detection method, and compute the accuracy and runtime speed on a GPU server. At the end, we show that the type of damage can be distinguished into eight types with acceptable accuracy by applying the proposed object detection method.

roaddamagedetection-deeplearning

It is intended to detect damage to road images taken by a camera. For this, deep learning technology, a subspace of machine learning, and Convolutional Neural Networks (CNN), one of the most popular types of deep neural networks, are used. The TensorFlow library is trained through the Ssd Inception V2 Coco pre-trained model to detect damage to images. As a result of the tests and trainings, the closest determinations are 86%. In order to increase the accuracy of the training, the use of GPU, the magnification of the data set and the number of iterations were considered.

rosco

A Reference Open Source Controller for Wind Turbines

rpi-robot

a raspberry pi robot which you can remote control over the internet

rrcnn

rtsnet_icassp22

Extend KalmanNet to smoothing

sequential_pinn

Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems

simple_dynamic_mooring_model

A simple dynamic mooring model based on Morison equation.

skyremoval

Create sky masks to improve photogrammetric reconstruction

sonig

Matlab source code for the SONIG algorithm: Sparse Online Noisy-Input Gaussian process regression.