ChronoCast: A time-series paradigm for molecular dynamics simulation using equivariant graph neural networks
- DOI
- 10.1103/ccl7-lx2b
- Published
- 2026-06-18
- Container
- Physical Review E
- Publisher
- American Physical Society (APS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1103/ccl7-lx2b,
title = {ChronoCast: A time-series paradigm for molecular dynamics simulation using equivariant graph neural networks},
author = {Yuxing Wang and Zhongwei Zhang and Shuang Lu and Shuyue Shan and Vitaly A. Kuzkin and Anton M. Krivtsov and Jie Chen},
year = {2026},
journal = {Physical Review E},
doi = {10.1103/ccl7-lx2b},
url = {https://doi.org/10.1103/ccl7-lx2b}
}RIS
TY - JOUR TI - ChronoCast: A time-series paradigm for molecular dynamics simulation using equivariant graph neural networks AU - Yuxing Wang AU - Zhongwei Zhang AU - Shuang Lu AU - Shuyue Shan AU - Vitaly A. Kuzkin AU - Anton M. Krivtsov AU - Jie Chen PY - 2026 JO - Physical Review E DO - 10.1103/ccl7-lx2b UR - https://doi.org/10.1103/ccl7-lx2b ER -
APA
Wang, Y., Zhang, Z., Lu, S., Shan, S., Kuzkin, V. A., Krivtsov, A. M., & Chen, J. (2026). ChronoCast: A time-series paradigm for molecular dynamics simulation using equivariant graph neural networks. Physical Review E. https://doi.org/10.1103/ccl7-lx2b
Source records
- crossref · retrieved 2026-11-10T09:17:47.472Z