This project is about implementing Park's (1994) algorithm for Optimal Latin Hypercube sampling in a python function.

Pytorch implementations of ConvLSTM and ConvGRU modules with examples

Using the Pytorch to build an image temporal prediction model of the encoder-forecaster structure, ConvGRU kernel & ConvLSTM kernel

Code used in Thesis "Convolutional Recurrent Neural Networks for Remaining Useful Life Prediction in Mechanical Systems".

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Multi-Scale Convolutional Recurrent Encoder-Decoder

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

deep learning for image processing including classification and object-detection etc.

stock predict with MLP,CNN,RNN,LSTM,Transformer and Transformer-LSTM

PyTorch-based Super-Resolution and Restoration Image Processing Module for VapourSynth

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Advers…

Data Integration Toolkit

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).

Official git for "CTAB-GAN: Effective Table Data Synthesizing"

tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).

Composition-Conditioned Crystal GAN pytorch code

PyTorch implementations of Generative Adversarial Networks.

Streamlit web application that uses trained models (e.g. CNNs) to classify digits drawn by users or generated by a Conditional-WGAN-GP. One can choose between models from Pytorch, Keras, and Scikit…

Simple Implementation of many GAN models with PyTorch.

Code for the Make Your Own Neural Network book

Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.

Chaospy - Toolbox for performing uncertainty quantification.

Bayes Net Toolbox for Matlab

Cross-platform download bilibili video desktop software, support windows, macOS, Linux

Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著

Synthetic data generators for tabular and time-series data

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

Building and training artificial neural networks (regression or classification) using the genetic algorithm.

Bachelor Degree Project in Information Technology