42 citations · 73 across the 4 of their papers we have counts for
6 papers
FoggySight: A Scheme for Facial Lookup Privacy
Ivan Evtimov, Pascal Sturmfels, Tadayoshi Kohno
Advances in deep learning algorithms have enabled better-than-human performance on face recognition tasks. In parallel, private companies have been scraping social media and other…
Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models
Pascal Sturmfels, Jesse Vig, Ali Madani +1
For protein sequence datasets, unlabeled data has greatly outpaced labeled data due to the high cost of wet-lab characterization. Recent deep-learning approaches to protein predict…
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks
Joseph D. Janizek, Pascal Sturmfels, Su-In Lee
Recent work has shown great promise in explaining neural network behavior. In particular, feature attribution methods explain which features were most important to a model's predic…
Improving performance of deep learning models with axiomatic attribution priors and expected gradients
Gabriel Erion, Joseph D. Janizek, Pascal Sturmfels +2
Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; these attribution priors optimize for a model whos…
A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images
Pascal Sturmfels, Saige Rutherford, Mike Angstadt +3
Given the wide success of convolutional neural networks (CNNs) applied to natural images, researchers have begun to apply them to neuroimaging data. To date, however, exploration o…
Select and Permute: An Improved Online Framework for Scheduling to Minimize Weighted Completion Time
Samir Khuller, Jingling Li, Pascal Sturmfels +2
In this paper, we introduce a new online scheduling framework for minimizing total weighted completion time in a general setting. The framework is inspired by the work of Hall et a…