Carlos Guestrin

Major Open-Source Projects

A significant focus of our research has been building and releasing ML systems that work in the real-world, with the aim of gaining massive adoption, impacting industry and fundamentally influencing the design and architecture of such systems. Here are some key projects we have co-created:

  • TVM: end-to-end deep learning compiler stack for CPUs, GPUs and specialized accelerators
  • Turi Create: simplifies the development of custom machine learning models
  • XGBoost: scalable, portable and distributed gradient boosting library
  • LIME: explaining the predictions of any machine learning classifier
  • MXNet: lightweight, portable, flexible distributed/mobile deep learning library (Apache incubated)
  • Core ML Tools: converter tools for Apple's Core ML framework
  • SFrame: scalable tabular and graph data-structures built for out-of-core data analysis and machine learning
  • GraphChi: large-scale graph computations on a single machine
  • GraphLab and PowerGraph: framework for large-scale machine learning and graph computation
  • Matlab Toolbox for Submodular Function Optimization