8 citations · 11 across the 6 of their papers we have counts for
6 papers
Open Vocabulary Compositional Explanations for Neuron Alignment
Biagio La Rosa, Leilani H. Gilpin
Neurons are the fundamental building blocks of deep neural networks, and their interconnections allow AI to achieve unprecedented results. Motivated by the goal of understanding ho…
Guaranteed Optimal Compositional Explanations for Neurons
Biagio La Rosa, Leilani H. Gilpin
Compositional explanations are a family of methods that aim to describe the spatial alignment between neurons' receptive field activations and concepts through logical rules, typic…
Explaining Deep Neural Networks by Leveraging Intrinsic Methods
Biagio La Rosa
Despite their impact on the society, deep neural networks are often regarded as black-box models due to their intricate structures and the absence of explanations for their decisio…
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa, Leilani H. Gilpin, Roberto Capobianco
Compositional Explanations is a method for identifying logical formulas of concepts that approximate the neurons' behavior. However, these explanations are linked to the small spec…
Detection Accuracy for Evaluating Compositional Explanations of Units
Sayo M. Makinwa, Biagio La Rosa, Roberto Capobianco
The recent success of deep learning models in solving complex problems and in different domains has increased interest in understanding what they learn. Therefore, different approa…
Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models
Biagio La Rosa, Roberto Capobianco, Daniele Nardi
Due to their black-box and data-hungry nature, deep learning techniques are not yet widely adopted for real-world applications in critical domains, like healthcare and justice. Thi…