1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 1 cited
A Maximum Log-Likelihood Method for Imbalanced Few-Shot Learning Tasks
Samuel Hess, Gregory Ditzler
Few-shot learning is a rapidly evolving area of research in machine learning where the goal is to classify unlabeled data with only one or "a few" labeled exemplary samples. Neural…
cs.LG2021
ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI
Samuel Hess, Gregory Ditzler
Unexplainable black-box models create scenarios where anomalies cause deleterious responses, thus creating unacceptable risks. These risks have motivated the field of eXplainable A…