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From Physics to Computer Science: Symmetry in Neural Networks with Prof. Tess Smidt

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Manage episode 474739341 series 3652300
Content provided by Department of Physics and Materials Science (DPhyMS) - University of Luxembourg, Department of Physics, and Materials Science (DPhyMS) - University of Luxembourg. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Department of Physics and Materials Science (DPhyMS) - University of Luxembourg, Department of Physics, and Materials Science (DPhyMS) - University of Luxembourg or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

For the second episode we had the privilege of speaking with Professor Tess Smidt, Assistant Professor at MIT who specializes in the fields of Euclidean symmetry and neural networks. From her early days when she majored in physics and minored in architecture, to her current work in computer science, Tess has always sought to understand how different fields can inform one another.

A particularly fascinating aspect of our conversation was Tess's focus on symmetry. She argues that incorporating symmetry into neural networks can lead to more effective learning and better outcomes in scientific modeling.

Coming Up: Don't miss Prof. Smidt's presentation "Harnessing Symmetry and AI for Designing Physical Systems" on 14th May 2025, at Novotel in Kirchberg, Luxembourg.

Join us at Physics for Future on May 14th and 15th for two days of groundbreaking discussions and discoveries. Secure your spot now—registrations are open at the University of Luxembourg: https://www.uni.lu/fstm-en/conferences/physics-for-future/.

Sound: Chasing vampires by Victor_Natas -- https://freesound.org/s/694474/ -- License: Attribution 4.0

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Manage episode 474739341 series 3652300
Content provided by Department of Physics and Materials Science (DPhyMS) - University of Luxembourg, Department of Physics, and Materials Science (DPhyMS) - University of Luxembourg. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Department of Physics and Materials Science (DPhyMS) - University of Luxembourg, Department of Physics, and Materials Science (DPhyMS) - University of Luxembourg or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

For the second episode we had the privilege of speaking with Professor Tess Smidt, Assistant Professor at MIT who specializes in the fields of Euclidean symmetry and neural networks. From her early days when she majored in physics and minored in architecture, to her current work in computer science, Tess has always sought to understand how different fields can inform one another.

A particularly fascinating aspect of our conversation was Tess's focus on symmetry. She argues that incorporating symmetry into neural networks can lead to more effective learning and better outcomes in scientific modeling.

Coming Up: Don't miss Prof. Smidt's presentation "Harnessing Symmetry and AI for Designing Physical Systems" on 14th May 2025, at Novotel in Kirchberg, Luxembourg.

Join us at Physics for Future on May 14th and 15th for two days of groundbreaking discussions and discoveries. Secure your spot now—registrations are open at the University of Luxembourg: https://www.uni.lu/fstm-en/conferences/physics-for-future/.

Sound: Chasing vampires by Victor_Natas -- https://freesound.org/s/694474/ -- License: Attribution 4.0

  continue reading

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