Code for "Is Mamba Effective for Time Series Forecasting?"

Simple, minimal implementation of the Mamba SSM in one file of PyTorch.

A simple and efficient Mamba implementation in pure PyTorch and MLX.

This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019

[IJCAI-24] Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting

This tool is developed for resetting Cursor editor device IDs to resolve account restrictions when switching accounts or during trial periods.

A curated collection of papers, tutorials, videos, and other valuable resources related to Mamba.

Top paper collection for stock price prediction, quantitative trading. Covering top conferences and journals like KDD, WWW, CIKM, AAAI, IJCAI, ACL, EMNLP.

Mamba SSM architecture

The code of PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability

This repository hosts the code for the SAMBA model, proposed in our IEEE ICASSP paper "Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction".

A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.

Official Implementation of STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model.

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the …

CNNpred: CNN-based stock market prediction using a diverse set of variables

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The implementation Code of CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement

[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)

FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs 🚀 🚀 🚀

A Library for Advanced Deep Time Series Models.

Code related to my YouTube vids!

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Locating and editing factual associations in GPT (NeurIPS 2022)

Relational Temporal Graph Convolutional Network for Ranking-based Stock Prediction