61 citations · 297 across the 23 of their papers we have counts for
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cs.LG2022★ 1 cited
Bounding generalization error with input compression: An empirical study with infinite-width networks
Angus Galloway, Anna Golubeva, Mahmoud Salem +3
Estimating the Generalization Error (GE) of Deep Neural Networks (DNNs) is an important task that often relies on availability of held-out data. The ability to better predict GE ba…
stat.ML2022★ 2 cited
The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization
Mufan Bill Li, Mihai Nica, Daniel M. Roy
The logit outputs of a feedforward neural network at initialization are conditionally Gaussian, given a random covariance matrix defined by the penultimate layer. In this work, we…