Downloads (1-5 of 5)

1. Supplementary Data for "An unsupervised machine learning based approach to identify efficient spin-orbit torque materials"

   Downloads | 18 Feb 2024 | Contributor(s):: Shehrin Sayed, Hannah Kleidermacher, Giulianna Hashemi-Asasi, Cheng-Hsiang Hsu, Sayeef Salahuddin

   Introduction:There has been a growing interest in materials with large spin-orbit torques (SOT) for many novel applications, and in our article [1], which is currently under review, we have shown that a machine-learning-based approach using a word embedding model can predict...

2. Scientific Text-Based Machine Learning

   Downloads | 02 Nov 2023 | Contributor(s):: Shehrin Sayed

   Please note that this page is under development and information provided may change. Introduction: Machine learning is undoubtedly a useful tool and is gradually changing how we function in everyday life. The application of this powerful tool in materials and devices research may have...

3. Optical MNIST dataset

   Downloads | 21 Apr 2022 | Contributor(s):: Hanyu Zheng

   Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in...

4. Literature transcriptomics review and data of Nanoparticle Induced Cellular Outcomes

   Downloads | 07 Mar 2019 | Contributor(s):: Irini Furxhi

   Data from in vitro differential gene expression analysis studies were gathered from peer-reviewed scientific literature. The studies gathered had a considerably variety of different human cell models including both primary cells and immortalized cell lines which exhibit varying...

5. Random Forest Model Objects for Pulmonary Toxicity Risk Assessment

   Downloads | 17 Apr 2013 | Contributor(s):: Jeremy M Gernand

   This download contains MATLAB treebagger or Random Forest (RF) model objects created via meta-analysis of nanoparticle rodent pulmonary toxicity experiments. The ReadMe.txt file contains object descriptions including output definitions, input parameter descriptions, and applicable limits.