Attention visualization
Attention visualization refers to techniques that represent and analyze the focus of attention in data, particularly in machine learning and cognitive science.
interpretability
Feature visualization
Feature visualization is a technique in machine learning that helps interpret complex models by visualizing the features learned by the model.
Counterfactual explanations
Counterfactual explanations provide insights into the decisions made by algorithms by illustrating what could have happened under different circumstances.
Ablation (neural network interpretability)
Ablation in neural network interpretability involves systematically removing components to assess their impact on model performance, aiding in understanding model decisions.
Concept activation vectors (CAV)
Concept activation vectors (CAV) are a method used in machine learning to interpret neural networks by associating specific directions in the latent space with human-understandable concepts.