2 citations · 3 across the 4 of their papers we have counts for
4 papers
GLARE: A Natural Language Interface for Querying Global Explanations
Bhavan Vasu, Rajesh Mangannavar
While global explanations are crucial for understanding vision models across datasets, classes, and decision contexts, their complex and monolithic nature often hinders practical e…
Local-to-Global Logical Explanations for Deep Vision Models
Bhavan Vasu, Giuseppe Raffa, Prasad Tadepalli
While deep neural networks are extremely effective at classifying images, they remain opaque and hard to interpret. We introduce local and global explanation methods for black-box…
Interactive Mars Image Content-Based Search with Interpretable Machine Learning
Bhavan Vasu, Steven Lu, Emily Dunkel +3
The NASA Planetary Data System (PDS) hosts millions of images of planets, moons, and other bodies collected throughout many missions. The ever-expanding nature of data and user eng…
Iterative and Adaptive Sampling with Spatial Attention for Black-Box Model Explanations
Bhavan Vasu, Chengjiang Long
Deep neural networks have achieved great success in many real-world applications, yet it remains unclear and difficult to explain their decision-making process to an end-user. In t…