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math.CV2021
Holomorphic feedforward networks
Michael R. Douglas
A very popular model in machine learning is the feedforward neural network (FFN). The FFN can approximate general functions and mitigate the curse of dimensionality. Here we introd…
math.CV2004★ 2 cited
Critical points and supersymmetric vacua, II: Asymptotics and extremal metrics
Michael R. Douglas, Bernard Shiffman, Steve Zelditch
Motivated by the vacuum selection problem of string/M theory, we study a new geometric invariant of a positive Hermitian line bundle over a compact Kähler manifold: t…
math.CV2004★ 121 cited
Critical points and supersymmetric vacua
Michael R. Douglas, Bernard Shiffman, Steve Zelditch
Supersymmetric vacua (`universes') of string/M theory may be identified with certain critical points of a holomorphic section (the `superpotential') of a Hermitian holomorphic line…