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Gradients for thermal state learning
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Classroom Contents
Training Quantum Neural Networks with an Unbounded Loss Function - IPAM at UCLA
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- 1 Overview
- 2 A new type of learning
- 3 Quantizing a feed-forward neural network
- 4 Unitary quantum neural network
- 5 Two components of trainings
- 6 Barren plateaus in QNNS
- 7 The big tradeoff in OML
- 8 Circumventing barren plateau
- 9 What does classical ML do?
- 10 Extended swap test
- 11 Learning thermal states
- 12 Generative algorithm to thermal state learning
- 13 Gradients for thermal state learning
- 14 Shallow algorithm
- 15 FT algorithm
- 16 Avoiding poor initializations
