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README.md

AI for Science

Contents

  • Computational Graph and optimal checkpointing (Julia)
  • Generative modeling
  • Random-batch meothods for interacting particle systems (Julia)

Reading

  • Book: Pattern recognition and machine learning1.
  • Book: The Elements of Differentiable Programming 2.
  • Book: Understanding molecular simulation: from algorithms to applications 3.

Researchers in the field

Projects

  • Reproduce: Ab-initio study of interacting fermions at finite temperature with neural canonical transformation4.
  • Reproduce: Random batch Ewald method for Coulomb interactions5.
  • Reproduce: Random-batch list algorithm for short-range molecular dynamics simulations6; and if time permits, its extension to the spring-bead model for polymer chains7.
  • Reproduce: Replica Monte Carlo Simulation of Spin-Glasses8.
  • Optimal checkpointing for non-uniform program (e.g. tensor network contraction)9.

References

Footnotes

  1. Bishop, Christopher M., 2006. Pattern recognition and machine learning.

  2. Blondel, M., Roulet, V., 2024. The Elements of Differentiable Programming. https://doi.org/10.48550/arXiv.2403.14606

  3. Frenkel, D. and Smit, B., 2023. Understanding molecular simulation: from algorithms to applications. Elsevier.

  4. Xie, H., Zhang, L., Wang, L., 2022. Ab-initio study of interacting fermions at finite temperature with neural canonical transformation. JML 1, 38–59. https://doi.org/10.4208/jml.220113

  5. S. Jin, L. Li, Z. Xu, and Y. Zhao, A random batch Ewald method for particle systems with Coulomb interactions, SIAM J. Sci. Comput., 43 (2021), pp. B937–B960.

  6. Liang, J., Xu, Z. and Zhao, Y., 2021. Random-batch list algorithm for short-range molecular dynamics simulations. The Journal of Chemical Physics, 155(4). https://doi.org/10.1063/5.0056515

  7. Kremer, K. and Grest, G.S., 1990. Dynamics of entangled linear polymer melts: A molecular‐dynamics simulation. The Journal of Chemical Physics, 92(8), pp.5057-5086. https://doi.org/10.1063/1.458541

  8. Swendsen, R.H. and Wang, J.S., 1986. Replica Monte Carlo simulation of spin-glasses. Physical review letters, 57(21), p.2607. https://doi.org/10.1103/PhysRevLett.57.2607

  9. Griewank, A., 1992. Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation. Optimization Methods and Software 1, 35–54. https://doi.org/10.1080/10556789208805505