We should be able to attach names to rules, so that normalization steps (and error messages?) can be better understood by users. For example:
normalize(@term(diff(x + y, x)))
- @term(diff(x,x) + diff(y,x)) by sum rule in differentiation
- @term(one(x) + diff(y, x)) by linear rule of differentiation
- @term(1 + diff(y, x)) by multiplicative identity of a number
- @term(1 + zero(x))
Implemented here a Binary Neural Network (BNN) achieving nearly state-of-art results but recorded a significant reduction in memory usage and total time taken during training the network.
ModelReduction is a repository of JuliaFEM to reduce the dimension of a model for multibody dynamics problems. The package includes e.g. the Guyan reduction and the Craig-Bampton method.
Attempting to generate the sphinx documentation fails.
The may be a configuration issue and/or a code documentation style issue.
We need to pick a format of code documatation that works (preferably astropy, or maybe numpy), convert all doc strings to it, and get the documentation working.
A fast framework for pre-processing (Cleaning text, Reduction of vocabulary, Feature extraction and Vectorization). Implemented with parallel processing using custom number of processes.
We should be able to attach names to rules, so that normalization steps (and error messages?) can be better understood by users. For example: