[1] F. Scarselli, M. Gori, A.C. Tsoi, M. Hagenbuchner, and G. Monfardini. The graph neural network model. IEEE Transactions on Neural Networks, 20(1):61 80, 2009.

These codes are pretty old. I no longer have MATLAB so I'm setting the repository to archive. These are functions I wrote during my post doc at USC (2009-2011) to work with receiver function data. It ...

Discover why researchers in high-energy physics rely on the GaGe RazorMax Express—an efficient, high-performance digitizer.

Abstract: Over the last few years, the malware propagation on PC platforms, especially on Windows OS has been even severe. For the purpose of resisting a large scale of malware variants, machine ...

Abstract: Achieving distributed reinforcement learning (RL) for large-scale cooperative multiagent systems (MASs) is challenging because: 1) each agent has access to only limited information and 2) ...

One powerful way to do this is through a routine called slow reveal graphs.

Comparing a map of the neurons in a nematode worm - the connectome - with a map of how signals travel across those neurons ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...

Developed during ten years of teaching experience, this book serves as a set of lecture notes for an introductory course on numerical computation, at the senior undergraduate level. These notes ...

We think of these as functions of ν with ρ, δ as parameters. The combinatorial exponent Ψ com involves a scaled, shifted version of the Shannon entropy, which is a symmetric, roughly parabolic shaped ...