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@AI4Science-WestlakeU

AI4Science-WestlakeU

README.md

AI for Scientific Simulation and Discovery Lab

Our research group at Westlake University (西湖大学) carries out long-term work on core and universal problems for AI + Science:

  • AI for scientific simulation, design, and control: Developing machine learning algorithms (based on Graph Neural Networks and Diffusion Models) for large-scale, multi-scale scientific simulation (applied to fluid dynamics, materials, plasmas), scientific design (protein design, materials design, mechanical design), and control (fluid control, PDE control);
  • AI for scientific discovery: Developing machine learning algorithms (based on foundation models and neuro-symbolic AI) to discover universal rules and internal structures in scientific systems (applied to life sciences and physics);

Group website: https://ai4s.lab.westlake.edu.cn/

Collaborators (a non-exhaustive list):

Popular repositories Loading

  1. cindm cindm Public

    [ICLR24] CinDM uses compositional generative models to design boundaries and initial states significantly more complex than the ones seen in training for physical simulation

    Jupyter Notebook 28 4

  2. diffphycon diffphycon Public

    [NeurIPS2024] DiffPhyCon uses generative models to control complex physical systems

    Jupyter Notebook 27 3

  3. beno beno Public

    [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values

    Python 22

  4. le-pde-uq le-pde-uq Public

    [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both forward and inverse problems.

    Jupyter Notebook 14

  5. research_toolbox research_toolbox Public

    A useful toolbox for research.

    9

  6. frontiers_in_AI_course frontiers_in_AI_course Public

    Jupyter Notebook 7

Repositories

Showing 10 of 10 repositories
  • MultiSimDiff Public
    AI4Science-WestlakeU/MultiSimDiff’s past year of commit activity
    Jupyter Notebook 1 MIT 0 0 0 Updated Dec 8, 2024
  • wdno Public

    Wavelet Diffusion Neural Operator (WDNO) uses diffusion models for generative PDE simulation and control.

    AI4Science-WestlakeU/wdno’s past year of commit activity
    2 MIT 0 0 0 Updated Dec 5, 2024
  • beno Public

    [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values

    AI4Science-WestlakeU/beno’s past year of commit activity
    Python 22 MIT 0 0 0 Updated Dec 5, 2024
  • diffphycon Public

    [NeurIPS2024] DiffPhyCon uses generative models to control complex physical systems

    AI4Science-WestlakeU/diffphycon’s past year of commit activity
    Jupyter Notebook 27 MIT 3 1 0 Updated Dec 5, 2024
  • .github Public
    AI4Science-WestlakeU/.github’s past year of commit activity
    0 0 0 0 Updated Nov 10, 2024
  • standard_repo Public template
    AI4Science-WestlakeU/standard_repo’s past year of commit activity
    Jupyter Notebook 3 0 0 0 Updated Sep 16, 2024
  • research_toolbox Public

    A useful toolbox for research.

    AI4Science-WestlakeU/research_toolbox’s past year of commit activity
    9 0 0 0 Updated Jul 10, 2024
  • cindm Public

    [ICLR24] CinDM uses compositional generative models to design boundaries and initial states significantly more complex than the ones seen in training for physical simulation

    AI4Science-WestlakeU/cindm’s past year of commit activity
    Jupyter Notebook 28 MIT 4 0 0 Updated May 1, 2024
  • frontiers_in_AI_course Public
    AI4Science-WestlakeU/frontiers_in_AI_course’s past year of commit activity
    Jupyter Notebook 7 MIT 0 0 0 Updated Mar 4, 2024
  • le-pde-uq Public

    [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both forward and inverse problems.

    AI4Science-WestlakeU/le-pde-uq’s past year of commit activity
    Jupyter Notebook 14 MIT 0 0 0 Updated Feb 26, 2024