no code implementations • 16 Apr 2024 • Alexey Kornaev, Elena Kornaeva, Oleg Ivanov, Ilya Pershin, Danis Alukaev
The proposed model regularizes uncertain predictions, and trains to calculate both the predictions and their uncertainty estimations.
2 code implementations • 23 Oct 2023 • Danis Alukaev, Semen Kiselev, Ilya Pershin, Bulat Ibragimov, Vladimir Ivanov, Alexey Kornaev, Ivan Titov
Concept Bottleneck Models (CBMs) assume that training examples (e. g., x-ray images) are annotated with high-level concepts (e. g., types of abnormalities), and perform classification by first predicting the concepts, followed by predicting the label relying on these concepts.