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Found 3 papers, 2 papers with code
Optimal Nonlinearities Improve Generalization Performance of Random Features
Random feature model with a nonlinear activation function has been shown to perform asymptotically equivalent to a Gaussian model in terms of training and generalization errors.
Neural Academic Paper Generation
In this work, we tackle the problem of structured text generation, specifically academic paper generation in $\LaTeX{}$, inspired by the surprisingly good results of basic character-level language models.
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning
Among those, CGF aims to produce new test inputs by fuzzing existing ones to achieve high coverage on a test adequacy criterion (i. e. coverage criterion).
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