Some papers were discussed by Kumar Shridhar :
Predictive Neural Networks : where the authors showed that linearly activated recurrent neural networks can approximate any time-dependent function f(t) given by a number of function values. The approximation can effectively be learned by simply solving a linear equation system; no backpropagation or similar methods are needed.
Adaptive Neural Compilation : where the authors showed that it is possible to compile programs written in a low-level language to a differentiable representation.
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