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Found 5 papers, 2 papers with code
Real-Time Personalization with Simple Transformers
However, these models struggle to capture complex user behaviors, which are essential for making accurate recommendations.
MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus Images
Existing multi-modal learning methods on fundus and OCT images mostly require both modalities to be available and strictly paired for training and testing, which appears less practical in clinical scenarios.
Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model
We tightly characterize, via a formal lower bound, the extent to which any algorithm can optimally leverage predictions (that is, to ``follow'' the predictions when accurate, and ``ignore'' them when inaccurate) without knowing the prediction accuracy or the underlying arrival model.
Vessel-Promoted OCT to OCTA Image Translation by Heuristic Contextual Constraints
Our TransPro method is primarily driven by two novel ideas that have been overlooked by prior work.
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
Neural networks have been rapidly expanding in recent years, with novel strategies and applications.
