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20202026
most citedConvergence to good non-optimal critical points in the training of neural networks: Gradient descent optimization with one random initialization overcomes all bad non-global local minima with high probability

2 citations · 4 across the 6 of their papers we have counts for

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math.NA2021★ 1 cited

Lower bounds for artificial neural network approximations: A proof that shallow neural networks fail to overcome the curse of dimensionality

Philipp Grohs, Shokhrukh Ibragimov, Arnulf Jentzen +1

Artificial neural networks (ANNs) have become a very powerful tool in the approximation of high-dimensional functions. Especially, deep ANNs, consisting of a large number of hidden…