applicable models
cnn
Techniques specifically designed for Convolutional Neural Networks
5 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Taylor Decomposition | Algorithmic | Neural Network CNN | Any | Taylor Decomposition is a mathematical technique that explains neural network predictions by computing first-order and... | ||
| Gradient-weighted Class Activation Mapping | Algorithmic | CNN | Image | Grad-CAM creates visual heatmaps showing which regions of an image a convolutional neural network focuses on when making... | ||
| Classical Attention Analysis in Neural Networks | Algorithmic | Rnn CNN | Any | Classical attention mechanisms in RNNs and CNNs create alignment matrices and temporal attention patterns that show how... | ||
| Concept Activation Vectors | Algorithmic | Neural Network Transformer +1 | Any | Concept Activation Vectors (CAVs), also known as Testing with Concept Activation Vectors (TCAV), identify mathematical... | ||
| Fair Adversarial Networks | Algorithmic | Neural Network CNN +1 | Any | An in-processing fairness technique that employs adversarial training with dual neural networks to learn fair... |
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