ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

Conference · Tue May 30 04:00:00 EDT 2017

DOI:https://doi.org/10.1145/3027063.3053103· OSTI ID:1361010

Hohman, Frederick M.; Hodas, Nathan O.; Chau, Duen Horng

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1361010
• Report Number(s): PNNL-SA-126087
• Country of Publication: United States
• Language: English