APA (7th ed.) Citation

Xue, T., Ooi, C. C., Ge, Z., Leong, F. Y., Li, H., & Kang, C. W. (2025). Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations.

Chicago Style (17th ed.) Citation

Xue, Tingkai, Chin Chun Ooi, Zhengwei Ge, Fong Yew Leong, Hongying Li, and Chang Wei Kang. Differentiable Physics-Neural Models Enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations. 2025.

MLA (9th ed.) Citation

Xue, Tingkai, et al. Differentiable Physics-Neural Models Enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations. 2025.