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Found 6 papers, 1 papers with code
Towards Modular Algorithm Induction
Main consists of a neural controller that interacts with a variable-length input tape and learns to compose modules together with their corresponding argument choices.
Deep Bayesian Convolutional Networks with Many Channels are Gaussian Processes
There is a previously identified equivalence between wide fully connected neural networks (FCNs) and Gaussian processes (GPs).
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
There is a previously identified equivalence between wide fully connected neural networks (FCNs) and Gaussian processes (GPs).
Sensitivity and Generalization in Neural Networks: an Empirical Study
In practice it is often found that large over-parameterized neural networks generalize better than their smaller counterparts, an observation that appears to conflict with classical notions of function complexity, which typically favor smaller models.
Code Synthesis with Priority Queue Training
We consider the task of program synthesis in the presence of a reward function over the output of programs, where the goal is to find programs with maximal rewards.
