Materials

Deep Multimodal Transfer-Learned Regression in Data-Poor Domains

In many real-world applications of deep learning, estimation of a target may rely on various types of input data modes, such as audio-video, image-text, etc. This task can be further complicated by a lack of sufficient data. Here we propose a Deep …

Semi-supervised learning approaches to class assignment in ambiguous microstructures

Uncovering links between processing conditions, microstructure, and properties is a central tenet of materials analysis. It is well known that microstructure determines properties, but expressing these structural features in a universal quantitative …