stem/AI/Neural Networks/CNN/GAN/GAN.md
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STEM/AI/Neural Networks/Activation Functions.md
STEM/AI/Neural Networks/CNN/FCN/FlowNet.md
STEM/AI/Neural Networks/CNN/FCN/ResNet.md
STEM/AI/Neural Networks/CNN/FCN/Skip Connections.md
STEM/AI/Neural Networks/CNN/GAN/DC-GAN.md
STEM/AI/Neural Networks/CNN/GAN/GAN.md
STEM/AI/Neural Networks/CNN/Interpretation.md
STEM/AI/Neural Networks/Deep Learning.md
STEM/AI/Neural Networks/MLP/Back-Propagation.md
STEM/AI/Neural Networks/MLP/MLP.md
STEM/AI/Neural Networks/Transformers/Attention.md
STEM/CS/ABI.md
STEM/CS/Calling Conventions.md
STEM/CS/Code Types.md
STEM/CS/Language Binding.md
STEM/img/am-regulariser.png
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# Fully Convolutional
- Remove [[Max Pooling]]
- Use strided [[upconv]]
- Remove [[MLP|FC]] layers
- Hurts convergence in non-classification
- Normalisation tricks
- Batch normalisation
- Batches of 0 mean and variance 1
- Leaky [[Activation Functions#ReLu|ReLu]]
# Stages
## Generator, G
- Synthesise 'fake' images
- From noise
## Discriminator, D
- Discriminator is a classifier
- Is image fake or real
![[gan-arch.png]]
![[gan-arch2.png]]
![[gan-results.png]]
# Training
![[gan-training-discriminator.png]]
![[gan-training-generator.png]]
# Code Vector Math for Control
![[cvmfc.png]]
- Do [[Interpretation#Activation Maximisation|AM]] to derive code for an image
![[code-vector-math-for-control-results.png]]