QuantumShellNet: ground-state eigenvalue prediction of materials using electronic shell structures and fermionic properties via convolutions
Efficient and precise characterization of material properties is critical in quantum mechanical
modeling. While Density Functional Theory (DFT) remains a foundational method for …
modeling. While Density Functional Theory (DFT) remains a foundational method for …
Multimodal neural network-based predictive modeling of nanoparticle properties from pure compounds
Simulating complex and large materials is a challenging task that requires extensive domain
knowledge and computational expertise. This study introduces Pure2DopeNet, an …
knowledge and computational expertise. This study introduces Pure2DopeNet, an …
A reinforcement learning approach to effective forecasting of pediatric hypoglycemia in diabetes I patients using an extended de Bruijn graph
Pediatric diabetes I is an endemic and an especially difficult disease; indeed, at this point,
there does not exist a cure, but only careful management that relies on anticipating …
there does not exist a cure, but only careful management that relies on anticipating …