minqi824,Mickey (Minqi),github

Glad to see you! 👋 Welcome to my (Minqi Jiang, 江敏祺 for Chinese) profile:

I'm a third-year PhD candidate in Shanghai University of Finance and Economics (SUFE). At SUFE, I work with my PhD tutor Songqiao Han. I am glad to be a member of SUFE AI Lab (lead by professor Hailiang Huang). Currently, Anomaly Detection (aka Outlier Detection) is my major research direction, and I'm also interested in NLP and Quantitative Investment, see as follows:

Title	Research Direction	Conference/Journal	Paper	Code
ADGym: Design Choices for Deep Anomaly Detection	Anomaly Detection	NeurIPS 2023	📄	💻
Anomaly Detection with Score Distribution Discrimination	Anomaly Detection	KDD 2023	📄	💻
ADBench: Anomaly detection benchmark	Anomaly Detection	NeurIPS 2022	📄	💻
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection	NLP	IJCAI Workshop@LLM	📄	💻
An Improved Stacking Framework for Predicting Stock Price Index Direction	Quantitative Investment	Economic Computation & Economic Cybernetics Studies & Research	📄
An improved Stacking framework for stock index prediction by leveraging tree-based ensemble models and deep learning algorithms	Quantitative Investment	Physica A: Statistical Mechanics and its Applications	📄
An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models	Quantitative Investment	The Quarterly Review of Economics and Finance	📄

Quick links to know me better...

Mickey (Minqi)'s Projects

adbench

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

adgym

Official Implement of "ADGym: Design Choices for Deep Anomaly Detection", NeurIPS 2023

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

chatgpt-comparison-detection

ChatGPT Comparison Corpus (C3), Detectors, and more! 🔥

computer-vision

Deep Learning Algorithms in Computer Vision Domain

dlwithpytorch

Code to accompany my upcoming book "Deep learning with PyTorch Book " from Packt

gym

A toolkit for developing and comparing reinforcement learning algorithms.

icml2022-fedformer

Source code of ICML'22 paper: FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

overlap

Official code and data repository of "Anomaly Detection with Score Distribution Discrimination", KDD' 23.

paper-reading

深度学习经典、新论文逐段精读

sota-deep-anomaly-detection

List of implementation of SOTA deep anomaly detection methods

stockpredictionai

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 Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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