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Neural structure fields with application to crystal structure autoencoders

Engineering and Technology

Neural structure fields with application to crystal structure autoencoders

N. Chiba, Y. Suzuki, et al.

Discover how researchers Naoya Chiba, Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku, Kotaro Saito, and Kanta Ono are transforming crystal structure representation for machine learning with their innovative Neural Structure Fields (NeSF). This cutting-edge method uses neural networks to redefine material design, showcasing remarkable reconstruction capabilities compared to traditional grid-based techniques.... show more
Citation Metrics
Citations
3
Influential Citations
0
Reference Count
53
Citation by Year

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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