4 citations · 7 across the 5 of their papers we have counts for
3 papers · 1 filter
Towards Utilising a Range of Neural Activations for Comprehending Representational Associations
Laura O'Mahony, Nikola S. Nikolov, David JP O'Sullivan
Recent efforts to understand intermediate representations in deep neural networks have commonly attempted to label individual neurons and combinations of neurons that make up linea…
On the Detection of Anomalous or Out-Of-Distribution Data in Vision Models Using Statistical Techniques
Laura O'Mahony, David JP O'Sullivan, Nikola S. Nikolov
Out-of-distribution data and anomalous inputs are vulnerabilities of machine learning systems today, often causing systems to make incorrect predictions. The diverse range of data…
Disentangling Neuron Representations with Concept Vectors
Laura O'Mahony, Vincent Andrearczyk, Henning Muller +1
Mechanistic interpretability aims to understand how models store representations by breaking down neural networks into interpretable units. However, the occurrence of polysemantic…