andy
33ac3007bc
Affected files: .obsidian/graph.json .obsidian/workspace-mobile.json .obsidian/workspace.json 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 STEM/img/skip-connections.png
33 lines
1.1 KiB
Markdown
33 lines
1.1 KiB
Markdown
# Activation Maximisation
|
|
- Synthesise an ideal image for a class
|
|
- Maximise 1-hot output
|
|
- Maximise [[Activation Functions#SoftMax|SoftMax]]
|
|
|
|
![[am.png]]
|
|
- **Use trained network**
|
|
- Don't update weights
|
|
- [[Architectures|Feedforward]] noise
|
|
- [[Back-Propagation|Back-propagate]] [[Deep Learning#Loss Function|loss]]
|
|
- Don't update weights
|
|
- Update image
|
|
|
|
![[am-process.png]]
|
|
## Regulariser
|
|
- Fit to natural image statistics
|
|
- Prone to high frequency noise
|
|
- Minimise
|
|
- Total variation
|
|
- $x^*$ is the best solution to minimise [[Deep Learning#Loss Function|loss]]
|
|
|
|
$$x^*=\text{argmin}_{x\in \mathbb R^{H\times W\times C}}\mathcal l(\phi(x),\phi_0)$$
|
|
- Won't work
|
|
$$x^*=\text{argmin}_{x\in \mathbb R^{H\times W\times C}}\mathcal l(\phi(x),\phi_0)+\lambda\mathcal R(x)$$
|
|
- Need a regulariser like above
|
|
|
|
![[am-regulariser.png]]
|
|
|
|
$$\mathcal R_{V^\beta}(f)=\int_\Omega\left(\left(\frac{\partial f}{\partial u}(u,v)\right)^2+\left(\frac{\partial f}{\partial v}(u,v)\right)^2\right)^{\frac \beta 2}du\space dv$$
|
|
|
|
$$\mathcal R_{V^\beta}(x)=\sum_{i,j}\left(\left(x_{i,j+1}-x_{ij}\right)^2+\left(x_{i+1,j}-x_{ij}\right)^2\right)^{\frac \beta 2}$$
|
|
- Beta
|
|
- Degree of smoothing |