ADCME: Your Gateway to Inverse Modeling with Physics Based Machine Learning
ADCME is an open-source Julia package for inverse modeling in scientific computing using automatic differentiation. The backend of ADCME is the high performance deep learning framework, TensorFlow, which provides parallel computing and automatic differentiation features based on computational graph, but ADCME augments TensorFlow by functionalities–-like sparse linear algebra–-essential for scientific computing. ADCME leverages the Julia environment for maximum efficiency of computing. Additionally, the syntax of ADCME is designed from the beginning to be compatible with the Julia syntax, which is friendly for scientific computing.
The tutorial does not assume readers with experience in deep learning. However, basic knowledge of scientific computing in Julia is required.
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