SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
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Updated
Jul 18, 2024 - HTML
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Special repository hosting the InPhyT website.
Blogging using Pluto.jl notebooks.
A Tutorial for Parallelised Scalable Simulations in TensorFlow
18.S096 - Applications of Scientific Machine Learning
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