Pinned Repositories
Adv-ALSTM
Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019
Autoformer
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
awesome-ai-in-finance
🔬 A curated list of awesome machine learning strategies & tools in financial market.
Financial-Data-Analysis
Interregional-Correlation-Analysis-of-Conronavirus-Confirmed-Cases-using-LSTM
kangmincho1
LTSF-NLinear-CryptoBot
NLinear-based Crypto Portfolio Management and Automated Trading
ShinhanAI-competition
Side-Projects
Collection of side projects
TIL
Today I Learned
kangmincho1's Repositories
kangmincho1/kangmincho1
kangmincho1/Side-Projects
Collection of side projects
kangmincho1/Adv-ALSTM
Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019
kangmincho1/Autoformer
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
kangmincho1/awesome-ai-in-finance
🔬 A curated list of awesome machine learning strategies & tools in financial market.
kangmincho1/deep-learning-time-series
List of papers, code and experiments using deep learning for time series forecasting
kangmincho1/Financial-Data-Analysis
kangmincho1/Interregional-Correlation-Analysis-of-Conronavirus-Confirmed-Cases-using-LSTM
kangmincho1/LTSF-NLinear-CryptoBot
NLinear-based Crypto Portfolio Management and Automated Trading
kangmincho1/ShinhanAI-competition
kangmincho1/TIL
Today I Learned
kangmincho1/Bi-Mamba4TS
kangmincho1/DoubleAdapt
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
kangmincho1/FEDformer
kangmincho1/Informer2020
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
kangmincho1/iTransformer
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting".
kangmincho1/kaggle
kangmincho1/LTSF-Linear
This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"
kangmincho1/mamba
kangmincho1/MambaStock
MambaStock: Selective state space model for stock prediction
kangmincho1/Nonstationary_Transformers
Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415
kangmincho1/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
kangmincho1/Pyraformer
kangmincho1/qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
kangmincho1/S-D-Mamba
Code for "Is Mamba Effective for Time Series Forecasting?"
kangmincho1/Stock-price-prediction-using-GAN
In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
kangmincho1/stocknet-code
Code for stock movement prediction from tweets and historical stock prices.
kangmincho1/Time-Series-Library
A Library for Advanced Deep Time Series Models.
kangmincho1/TimeGAN
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
kangmincho1/TimeMachine
TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting