17 citations · 17 across the 2 of their papers we have counts for
4 papers
Benchmarking Representation Learning for Natural World Image Collections
Grant Van Horn, Elijah Cole, Sara Beery +3
Recent progress in self-supervised learning has resulted in models that are capable of extracting rich representations from image collections without requiring any explicit label s…
On the Reproducibility of Neural Network Predictions
Srinadh Bhojanapalli, Kimberly Wilber, Andreas Veit +4
Standard training techniques for neural networks involve multiple sources of randomness, e.g., initialization, mini-batch ordering and in some cases data augmentation. Given that n…
Improving Calibration in Deep Metric Learning With Cross-Example Softmax
Andreas Veit, Kimberly Wilber
Modern image retrieval systems increasingly rely on the use of deep neural networks to learn embedding spaces in which distance encodes the relevance between a given query and imag…
Understanding Image Quality and Trust in Peer-to-Peer Marketplaces
Xiao Ma, Lina Mezghani, Kimberly Wilber +4
As any savvy online shopper knows, second-hand peer-to-peer marketplaces are filled with images of mixed quality. How does image quality impact marketplace outcomes, and can qualit…