2 papers
stat.ML2025
Probability Bounding: Post-Hoc Calibration via Box-Constrained Softmax
Kyohei Atarashi, Satoshi Oyama, Hiromi Arai +1
Many studies have observed that modern neural networks achieve high accuracy while producing poorly calibrated probabilities, making calibration a critical practical issue. In this…
cs.CV2023
Predicate Classification Using Optimal Transport Loss in Scene Graph Generation
Sorachi Kurita, Satoshi Oyama, Itsuki Noda
In scene graph generation (SGG), learning with cross-entropy loss yields biased predictions owing to the severe imbalance in the distribution of the relationship labels in the data…