1.3k citations · 2.9k across the 44 of their papers we have counts for
48 papers
Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm
D. P. Aguillard, T. Albahri, D. Allspach +188
We present a new measurement of the positive muon magnetic anomaly, , from the Fermilab Muon Experiment using data collected in 2019 and 2020. We ha…
Towards trustworthy seizure onset detection using workflow notes
Khaled Saab, Siyi Tang, Mohamed Taha +3
A major barrier to deploying healthcare AI models is their trustworthiness. One form of trustworthiness is a model's robustness across different subgroups: while existing models ma…
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays
Rogier van der Sluijs, Nandita Bhaskhar, Daniel Rubin +2
Image augmentations are quintessential for effective visual representation learning across self-supervised learning techniques. While augmentation strategies for natural imaging ha…
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models
Siyi Tang, Jared A. Dunnmon, Liangqiong Qu +4
Multivariate biosignals are prevalent in many medical domains, such as electroencephalography, polysomnography, and electrocardiography. Modeling spatiotemporal dependencies in mul…
ATCON: Attention Consistency for Vision Models
Ali Mirzazadeh, Florian Dubost, Maxwell Pike +4
Attention--or attribution--maps methods are methods designed to highlight regions of the model's input that were discriminative for its predictions. However, different attention ma…
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Minhaj Nur Alam, Rikiya Yamashita, Vignav Ramesh +6
Self supervised contrastive learning based pretraining allows development of robust and generalized deep learning models with small, labeled datasets, reducing the burden of label…