Runze Yang

Fast prediction of FCC regenerator temperature fields using digital – twin based on convolutional autoencoder dimensionality reduction and machine learning

Ahmad Alsuwaidi, John Nikko V. Salvilla, Jackie Rong, Mohamed Atef, Runze Yang, Qianqian Liu, et al.

Towards Voxel Spacing Consistency for Medical Image Segmentation

Xin You, Runze Yang, Minghui Zhang, Hanxiao Zhang, Han Li, Yi Yu, et al.

Volumetric medical image segmentation is essential for both preoperative diagnosis and intraoperative guidance. While recent years have witnessed rapid progress in segmentation architectures, comparatively little attention is paid to the physical voxel spacing of anatomical data.…Read more

Beyond Output-Space Calibration: Spectral Evidence Bundling for Selective Reliability Estimation in Time-Series Classification

Filippo Cenacchi, Longbing Cao, Runze Yang

Post-hoc calibration for time-series classification usually remaps output scores, but deployment decisions such as trust, abstention, and review depend on whether a confident prediction is supported by the current temporal signal. We address three time-series reliability gaps: id…Read more

FALCON-Discover: Discovering Concentrated False-Confidence Regions for Calibration

Filippo Cenacchi, Longbing Cao, Runze Yang

Calibration is usually evaluated in aggregate, but the most dangerous failures are often local: predictions that remain highly confident despite being wrong. We study this failure mode as false-confidence concentration, the extent to which confident errors occupy compact, discove…Read more