Brian DeCost

机构：Material Measurement Laboratory, Carnegie Mellon University · ORCID：0000-0002-3459-5888

发表论文 100 篇 · 总被引 5697 次 · h-index 26

代表论文

• Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets (2024 · npj Computational Materials · 被引 90)
• Probing out-of-distribution generalization in machine learning for materials (2025 · Communications Materials · 被引 64)
• Accelerating defect predictions in semiconductors using graph neural networks (2024 · APL Machine Learning · 被引 37)
• Efficient first principles based modeling via machine learning: from simple representations to high entropy materials (2024 · Journal of Materials Chemistry A · 被引 23)
• Probing out-of-distribution generalization in machine learning for materials (2024 · arXiv (Cornell University) · 被引 8)
• High-throughput aqueous passivation behavior of thin-film vs. bulk multi-principal element alloys in sulfuric acid (2024 · Corrosion Science · 被引 7)