This repository contains the code for the Implementation of the research paper "Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks" (CVPR 2022) done as a coursework in the course Deep Learning under the supervision of Dr. Mayank Vatsa.
Authors of University of Trento - Department of Information Engineering and Computer Science - DISIVia Sommarive, 9, 38123 Povo, Trento TN:
- Nicola Garau
- Niccol ́o Bisagno
- Zeno Sambugaro
- Nicola Conci
- The paper discusses theinterpretability and understanding of the network's response to a given input limitations of current neural network topologies.
- The paper introduces Agglomerator, a framework that organizes input distribution.