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The advent of larger datasets in materials science poses unique challenges in modeling, infrastructure, and data diversity and quality.
FOS: Computer and information sciences, Condensed Matter - Materials Science, Computer Science - Machine Learning, ddc:540, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Machine Learning (stat.ML), Computational Physics (physics.comp-ph), Machine Learning (cs.LG), 540 Chemie und zugeordnete Wissenschaften, Statistics - Machine Learning, Physics - Computational Physics
FOS: Computer and information sciences, Condensed Matter - Materials Science, Computer Science - Machine Learning, ddc:540, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Machine Learning (stat.ML), Computational Physics (physics.comp-ph), Machine Learning (cs.LG), 540 Chemie und zugeordnete Wissenschaften, Statistics - Machine Learning, Physics - Computational Physics
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |