341 citations · 937 across the 30 of their papers we have counts for
5 papers · 1 filter
mage: Fluid Moves Between Code and Graphical Work in Computational Notebooks
Mary Beth Kery, Donghao Ren, Fred Hohman +3
We aim to increase the flexibility at which a data worker can choose the right tool for the job, regardless of whether the tool is a code library or an interactive graphical user i…
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
Nilaksh Das, Haekyu Park, Zijie J. Wang +4
Deep neural networks (DNNs) are now commonly used in many domains. However, they are vulnerable to adversarial attacks: carefully crafted perturbations on data inputs that can fool…
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
Zijie J. Wang, Robert Turko, Omar Shaikh +5
Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first…
CNN 101: Interactive Visual Learning for Convolutional Neural Networks
Zijie J. Wang, Robert Turko, Omar Shaikh +5
The success of deep learning solving previously-thought hard problems has inspired many non-experts to learn and understand this exciting technology. However, it is often challengi…
Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning
Nilaksh Das, Haekyu Park, Zijie J. Wang +4
Deep neural networks (DNNs) are increasingly powering high-stakes applications such as autonomous cars and healthcare; however, DNNs are often treated as "black boxes" in such appl…