SIMIS-APCTP meeting: AI methods in Theoretical Physics
18F Conference Hall
SIMIS
Artificial intelligence (AI), machine learning (ML), and deep learning (DL) provide a broad array of very powerful tools which can be used to tackle a wide variety of problems in theoretical high-energy physics. The two-day (mini) SIMIS-APCTP workshop on “AI methods in Theoretical Physics” will host talks from Theoretical Physics researchers whose current research focuses on the application and development of AI methods in High-Energy Theoretical Physics. Indicative topics include the identification and classification of Calabi-Yau geometric structures, the reconstruction of holographic geometries from boundary data sets, as well as the solution of key equations of Theoretical Physics such as the Bethe or the Yang-Baxter equations with the use of AI techniques.
