Brain metastasis (BM) is a devastating complication of breast cancer (BC) with a poor prognosis. Early identification of high-risk patients is essential but currently lacks accurate predictive tools. This study aimed to develop a stable machine learning model for predicting BM in…
Spatial consistency is a fundamental physical property of wireless channels that reflects the smooth evolution of the channel between spatial locations. At the cluster level, it requires similar multipath components (MPCs) remain grouped into the same clusters as the transceivers…
Operator learning for partial differential equations (PDEs) on arbitrary geometries builds fast neural surrogates for large-scale simulation. Although recent geometry-adaptive neural operators have made substantial progress, they are mainly designed for forward problems in which…
Dual-energy CT (DECT) exploits attenuation differences across different X-ray spectra to provide richer material information and has been widely used in medical imaging. While sparse-view acquisition can lower radiation exposure, it makes DECT material decomposition even more cha…
Machine learning (ML) on tabular data is ubiquitous, yet obtaining abundant high-quality tabular data for model training remains a significant obstacle. Numerous works have focused on tabular data augmentation (TDA) to enhance the original table with additional data, thereby impr…
With the continued advancement of shale gas development, the issue of frac hit has become increasingly prominent and has emerged as a key factor influencing the production of shale gas wells. Quantitative evaluation of the impact of frac hit on shale gas wells and proposing diffe…