applicable models
model internals
Requires access to weights, neurons, or internal representations
17 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| DeepLIFT | Algorithmic | Requirements/model Internals Architecture/neural Networks +2 | Any | DeepLIFT (Deep Learning Important FeaTures) explains a single prediction of a neural network by dividing the difference... | ||
| Layer-wise Relevance Propagation | Algorithmic | Requirements/model Internals Architecture/neural Networks +3 | Any | Layer-wise Relevance Propagation (LRP) explains a neural network's prediction by working backwards from the output to... | ||
| Taylor Decomposition | Algorithmic | Requirements/model Internals Architecture/neural Networks +3 | Any | Taylor Decomposition explains one prediction of a neural network by splitting its output score into a contribution from... | ||
| Gradient Saliency | Algorithmic | Architecture/neural Networks Requirements/differentiable +2 | Image | Gradient saliency (also called vanilla gradient saliency) is the simplest gradient-based explanation for image... | ||
| Gradient-weighted Class Activation Mapping | Algorithmic | Architecture/neural Networks/convolutional Requirements/architecture Specific +3 | Image | Grad-CAM (Gradient-weighted Class Activation Mapping) draws a heatmap over an image showing which regions most raise a... | ||
| Attention Weight Analysis | Algorithmic | Architecture/neural Networks/recurrent Architecture/neural Networks/transformer +2 | Image Text | Attention weight analysis reads the weights an attention-based neural network assigns to the parts of its input, to see... | ||
| Monte Carlo Dropout | Algorithmic | Architecture/neural Networks Paradigm/probabilistic +4 | Any | Monte Carlo dropout estimates how uncertain a neural network is about each prediction. Dropout randomly switches off... | ||
| Temperature Scaling | Algorithmic | Architecture/neural Networks Paradigm/discriminative +4 | Any | Temperature scaling is a correction applied after training to a classifier that is more confident than it is accurate, a... | ||
| Monotonicity Constraints | Algorithmic | Architecture/neural Networks Architecture/probabilistic/gaussian Processes +3 | Tabular | Monotonicity constraints require a model's prediction to move only one way as a chosen input rises, with the other... | ||
| Neuron Activation Analysis | Algorithmic | Architecture/neural Networks Requirements/model Internals +1 | Text | Neuron activation analysis examines when individual neurons in a neural network respond strongly. The analyst runs a set... | ||
| Causal Mediation Analysis in Language Models | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +3 | Text | Causal mediation analysis traces which internal components of a language model carry the effect of a change in the input... | ||
| Concept Activation Vectors | Algorithmic | Architecture/neural Networks Requirements/gradient Access +2 | Any | A concept activation vector (CAV) is a direction inside a neural network that stands for a human idea such as 'stripes'.... | ||
| Learning Adversarially Fair and Transferable Representations | Algorithmic | Architecture/neural Networks Paradigm/parametric +4 | Image Tabular | Learning Adversarially Fair and Transferable Representations (LAFTR) trains an encoder that turns each record into a... | ||
| Embedding Bias Analysis | Testing | Architecture/neural Networks Architecture/neural Networks/transformer +3 | Text Image | Embedding bias analysis tests whether the numerical representations a model uses for words, images or documents link... | ||
| Machine Unlearning | Algorithmic | Architecture/model Agnostic Architecture/neural Networks +2 | Any | Machine unlearning removes the influence of specific training records from a trained model, so that the model behaves as... | ||
| Sanity Checks for Saliency Maps | Testing | Architecture/neural Networks Requirements/white Box +1 | Image Tabular Time-series | Sanity checks for saliency maps are two randomisation tests that show whether an explanation method's output depends on... | ||
| Sparse Autoencoder Feature Analysis | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +2 | Text | Sparse autoencoder feature analysis looks for human-interpretable units inside a neural network, usually a language... |
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