743 citations · 803 across the 17 of their papers we have counts for
4 papers · 1 filter
Towards falsifiable interpretability research
Matthew L. Leavitt, Ari Morcos
Methods for understanding the decisions of and mechanisms underlying deep neural networks (DNNs) typically rely on building intuition by emphasizing sensory or semantic features of…
Linking average- and worst-case perturbation robustness via class selectivity and dimensionality
Matthew L. Leavitt, Ari Morcos
Representational sparsity is known to affect robustness to input perturbations in deep neural networks (DNNs), but less is known about how the semantic content of representations a…
On the relationship between class selectivity, dimensionality, and robustness
Matthew L. Leavitt, Ari S. Morcos
While the relative trade-offs between sparse and distributed representations in deep neural networks (DNNs) are well-studied, less is known about how these trade-offs apply to repr…
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs
Matthew L. Leavitt, Ari Morcos
The properties of individual neurons are often analyzed in order to understand the biological and artificial neural networks in which they're embedded. Class selectivity-typically…