Elf Ua

"ELF," across various research domains, refers to a family of algorithms and frameworks designed to improve efficiency and accuracy in diverse machine learning tasks. Current research focuses on developing novel architectures, such as multi-level representation learning and meta-learning approaches, to address challenges in areas ranging from materials science (electrolyte design) to computer vision (gaze estimation and image deraining). These advancements aim to reduce reliance on extensive labeled datasets, improve model adaptability, and ultimately enhance the performance and applicability of machine learning models in various fields.