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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")
- (PureBasic)
- (Python)
- + 1
3
110
MOTrainer
Measurement Operator Trainer for data assimilation purposes.
- Data assimilation
- High performance computing
- Machine learning
- + 2
- ("Jupyter Notebook")
- (Python)
- (Shell)
- + 1
7
2
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
- (Markdown)
- (Other)
- (Python)
1
0
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
- (Markdown)
- (Other)
- (Python)
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