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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.

  • Updated Jul 4, 2024
  • Python
go-peer

🔐 🕵🏻 End-to-End encryption and Theoretically-Provable anonymity in a library wrapper. Confirmed by theoretical and research papers. The Hidden Lake anonymous network is located inside the project: https://github.com/number571/go-peer/tree/master/cmd/hidden_lake

  • Updated Jul 4, 2024
  • Go

Research on the spread of online media on X (formerly Twitter). Can we observe differences in the spread of fake and real news? Do users who spread fake/real news gain more of a following? Are real articles more popular than fake ones? Along with this, a neural network will be made to predict varality of an article based on its content.

  • Updated Jul 4, 2024
  • Python

The repository hosts the code, data, and other artefacts for the paper "A deep learning-based approach for identifying unresolved questions on Stack Exchange Q&A communities through graph-based communication modelling", available here: https://link.springer.com/article/10.1007/s41060-023-00454-0

  • Updated Jul 3, 2024
  • Jupyter Notebook

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