Bridging Deep Learning and Many-Body Quantum Physics via Tensor Networks

Bridging Deep Learning and Many-Body Quantum Physics via Tensor Networks

APS Physics via YouTube Direct link

Controlling Dependencies -Layer Widths

7 of 12

7 of 12

Controlling Dependencies -Layer Widths

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Bridging Deep Learning and Many-Body Quantum Physics via Tensor Networks

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 Machine Learning and Many-Body Physics
  3. 3 Baseline Architecture - Convolutional Arithmetic Circuit
  4. 4 Baseline Architecture. Convolutional Arithmetic Circuit
  5. 5 Baseline Architecture - Recurrent Arithmetic Circuit
  6. 6 Measures of Entanglement for Deep Learning Archs
  7. 7 Controlling Dependencies -Layer Widths
  8. 8 Start-End Entanglement in Recurrent Networks
  9. 9 Exponential Memory Capacity for Deep Networks
  10. 10 TN Constructions of Prominent Deep Learning Archs
  11. 11 Information Re-Use Vs. Loops
  12. 12 Results - Deep Learning Archs Support High Entanglement

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.