Pinned Repositories
Awesome-Large-Models-for-Time-Series
Papers for LLM and foundation models for time series analytics
awesome-ml-data-quality-papers
Papers about training data quality management for ML models.
DoubleAdapt
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
interpreters
LIFT
The official implementation of LIFT (ICLR'24). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators.
MASTER
This is the official code and supplementary materials for our AAAI-2024 paper: MASTER: Market-Guided Stock Transformer for Stock Price Forecasting. MASTER is a stock transformer for stock price forecasting, which models the momentary and cross-time stock correlation and guide feature selection with market information.
qlib
This forked repo additionally includes our DoubleAdapt (KDD'23) and MASTER (AAAI'24) for re-experiment.
Quant-Reading-List
Papers for AI + quantitative investment
StockMixer
Official code implementation of AAAI 2024 paper "StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting".
SUNNY-GNN
The official implementation of AAAI'24 paper: Self-Interpretable Graph Learning with Sufficient and Necessary Explanations.
SJTU-Quant's Repositories
SJTU-Quant/MASTER
This is the official code and supplementary materials for our AAAI-2024 paper: MASTER: Market-Guided Stock Transformer for Stock Price Forecasting. MASTER is a stock transformer for stock price forecasting, which models the momentary and cross-time stock correlation and guide feature selection with market information.
SJTU-Quant/qlib
This forked repo additionally includes our DoubleAdapt (KDD'23) and MASTER (AAAI'24) for re-experiment.
SJTU-Quant/DoubleAdapt
The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.
SJTU-Quant/StockMixer
Official code implementation of AAAI 2024 paper "StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting".
SJTU-Quant/Quant-Reading-List
Papers for AI + quantitative investment
SJTU-Quant/LIFT
The official implementation of LIFT (ICLR'24). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators.
SJTU-Quant/awesome-ml-data-quality-papers
Papers about training data quality management for ML models.
SJTU-Quant/SUNNY-GNN
The official implementation of AAAI'24 paper: Self-Interpretable Graph Learning with Sufficient and Necessary Explanations.
SJTU-Quant/interpreters
SJTU-Quant/Awesome-Large-Models-for-Time-Series
Papers for LLM and foundation models for time series analytics