MinKim's repositories
timeseries-clustering-vae
Variational Recurrent Autoencoder for timeseries clustering in pytorch
awesome-nas-papers
Awesome Neural Architecture Search Papers
CBAM.PyTorch
Non-official implement of Paper：CBAM: Convolutional Block Attention Module
CM-NAS
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)
cnn-lstm
CNN LSTM architecture implemented in Pytorch for Video Classification
CNNpred-pytorch
CNNpred: CNN-based stock market prediction using a diverse set of variables
covid-19-forecasting
Improving Neural Networks for Time-Series Forecasting using Data Augmentation and AutoML
darts-1
Differentiable architecture search for convolutional and recurrent networks
ENAS-pytorch
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
Getting-Things-Done-with-Pytorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Global-Flow-Local-Attention
The source code for paper "Deep Image Spatial Transformation for Person Image Generation"
nerf-pytorch
A PyTorch re-implementation of Neural Radiance Fields
Pytorch-CNN-with-cats-and-dogs-
Classification of cats and dogs using Pytorch
PyTorch-Radial-Basis-Function-Layer
An implementation of an RBF layer/module using PyTorch.
pytorch_wavelets
Pytorch implementation of 2D Discrete Wavelet (DWT) and Dual Tree Complex Wavelet Transforms (DTCWT) and a DTCWT based ScatterNet
ResNeSt
ResNeSt: Split-Attention Networks
Self-Attention-GAN
Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN)
ST-TR
Spatial Temporal Transformer Network for Skeleton-Based Activity Recognition
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stock-price-prediction
In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US stock market.
Stock_Support_Resistance_ML
Using Unsupervised learning, K-means, to determine stock support and resistance levels. Great for trading algorithms/bots using time serial analysis.
Time-Series-Transformer
A data preprocessing package for time series data. Design for machine learning and deep learning.
Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
transformer
Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.
transformer-blocks
Multi-head attention blocks in PyTorch.
Transformer_Timeseries
Pytorch code for Google's Temporal Fusion Transformer