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RESULTS ON SYNTHETIC DATASETS FOR GHZ STATES
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Classroom Contents
Learning Quantum with Generative Models
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- 1 Intro
- 2 MACHINE LEARNING/MANY-BODY PHYSICS FRIENDS
- 3 FLUCTUATIONS HANDWRITTEN DIGITS (MNIST)
- 4 ANALYTICAL UNDERSTANDING WHAT DOES THE CAN USE TO MAKE PREDICTIONS?
- 5 EXTENDING RESTRICTED BOLTZMANN MACHINES TO THE QUANTUM DOMAIN
- 6 NEURAL NETWORK QUANTUM STATES
- 7 NEED TO GO BEYOND STANDARD QUANTUM STATE TOMOGRAPHY
- 8 RESULTS ON SYNTHETIC DATASETS FOR GHZ STATES
- 9 RECURRENT NEURAL NETWORK MODEL AND RESULTS
- 10 NUMERICAL INVESTIGATION OF THE SAMPLE COMPLEXITY OF LEARNING
- 11 GROUND STATES OF LOCAL HAMILTONIANS
