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1-5 of 5

GrainLearning

Unsure about the parameters of your grains in a computer simulation? Use Iterative Bayesian Filtering to learn parameter distributions from limited data. Is your model running slowly? Speed up your simulations with machine-learning surrogates. All these features are integrated within GrainLearning.

  • Bayesian Inference
  • Data assimilation
  • Machine learning
  • + 2
  • Jupyter Notebook
  • Python
  • PureBasic
  • + 1
3
100

MOTrainer

Measurement Operator Trainer for data assimilation purposes.

  • Data assimilation
  • High performance computing
  • Machine learning
  • + 2
  • Jupyter Notebook
  • Python
  • TeX
  • + 1
7
2
Logo for Particle filter code with an example of subsidence caused by a compacting reservoir

Particle filter code with an example of subsidence caused by a compacting reservoir

Particle filter code with an example of subsidence caused by a compacting reservoir

  • Data assimilation
  • Particle filter
  • Reservoir compaction
  • + 1
  • Other
  • Python
  • Markdown
1
0
Logo for Partile filter code  with an example of weight collapse in importance sampling methods

Partile filter code with an example of weight collapse in importance sampling methods

Partile filter code with an example of weight collapse in importance sampling methods

  • Data assimilation
  • Importance sampling
  • Particle method
  • + 2
  • Python
  • Other
  • Markdown
1
0

ParticleDA.jl

Julia package to perform data assimilation with particle filters, supporting both thread-based parallelism and distributed processing using MPI.

  • Data assimilation
  • Julia Package
  • Particle filter
  • Julia
  • Jupyter Notebook
  • Shell
4
0