The Physics of Learning and The Learning of Physics

Explore AI applications in the natural sciences and economics at this Institute for Foundations of Machine Learning seminar.

Register to attend.

Tal Kachman, Professor at Radboud University, Visiting Professor at the Yale School of Management, Quantitative Researcher at Optiver, leads the complex learning lab doing research into the fundamentals of learning theory and its application to different domains such as economics, physics and chemistry.

AI has become all-encompassing in our society, it touches every technological aspect of our life, yet there is still a big gap in our fundamental understanding of how it can be used for the natural sciences. Under the umbrella of a recently received Nationaal Groeifonds grant for the creation of a chemical autonomas laboratories, Kachman will give an overview of several use cases where AI algorithms can help us solve problems in the natural sciences, from material discovery to synthesis, using both techniques from NeuralODE and Generative models with novel physics informed data generation models.

Friday, April 26 at 12:15pm to 1:00pm

Gates Dell Complex (GDC), 6.302
2317 SPEEDWAY , Austin, Texas 78712

Event Type

Campus & Community, Year of AI, Technical Talk

Departments

College of Natural Sciences

Tags

artificial intelligence

Website

https://ifml.institute/events/physics...

Group
Year of AI
Hashtag

#TexasAI

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