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GSNP Short Course on Adventures with Computational Modeling and Machine Learning

From Grains to Bits (Part II): Information Theory in Machine Learning and Physics

Room 222/223, Caesars Forum Convention Center

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  • Students: $40
  • Early Career: $60
  • Regular Members: $75
  • Non-APS Members: $100

Additional Details

  • Attendees may register for this event only or may register to attend in addition to their March Meeting 2023 registration.
  • This event is sponsored by Statistical and Nonlinear Physics (GSNP).


Information theory concerns the relationship between data, models, and reality. Its striking generality allows information theory to show up in a myriad of places and lend a powerfully unifying perspective. As such, it serves as a critical bridge to bring physicists to the issues of today. It is, first and foremost, the language of deep learning and therefore a route to using and understanding the capacities of modern AI — undoubtedly a timely matter.

It is also the language of model forming and model evaluation, be it a human’s imperfect model of reality influenced by social media or a trillion-parameter language model containing hidden biases, or a policy-guiding model of climate change. This tutorial will showcase a range of ways to bring ideas from information theory to the understanding of models and will serve as a rich foray into the topic to excite all levels of background.

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Registration for March Meeting 2023 is now open.

Pre-Meeting Short Courses and Tutorials

Join APS units before March Meeting 2023 for informative sessions about timely topics in physics.