17 citations · 17 across the 3 of their papers we have counts for
3 papers
ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data
Maya Varma, Jean-Benoit Delbrouck, Sarah Hooper +2
Vision-language models (VLMs), such as CLIP and ALIGN, are generally trained on datasets consisting of image-caption pairs obtained from the web. However, real-world multimodal dat…
Assessing Robustness to Noise: Low-Cost Head CT Triage
Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren +4
Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems w…
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
Daniel Y. Fu, Mayee F. Chen, Frederic Sala +3
Weak supervision is a popular method for building machine learning models without relying on ground truth annotations. Instead, it generates probabilistic training labels by estima…