3 papers
cs.LG2026
PG-KINN: A Physics-Informed Petrov-Galerkin Kolmogorov-Arnold Network for Solving Forward and Inverse PDEs
Amirhossein Sadr, Nima Soltani, Vahideh Moghtadaiee +3
Physics-informed learning of partial differential equations (PDEs) has been dominated by multilayer perceptrons (MLPs), whose spectral bias and dense parameterization limit both ac…
cs.AR2025
Modeling and Simulation Frameworks for Processing-in-Memory Architectures
Mahdi Aghaei, Saba Ebrahimi, Mohammad Saleh Arafati +4
Processing-in-Memory (PIM) has emerged as a promising computing paradigm to address the memory wall and the fundamental bottleneck of the von Neumann architecture by reducing costl…
cs.CV2025
GraphDerm: Fusing Imaging, Physical Scale, and Metadata in a Population-Graph Classifier for Dermoscopic Lesions
Mehdi Yousefzadeh, Parsa Esfahanian, Sara Rashidifar +5
Introduction. Dermoscopy aids melanoma triage, yet image-only AI often ignores patient metadata (age, sex, site) and the physical scale needed for geometric analysis. We present Gr…