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Log-sum-exp neural networks and posynomial models for convex and
  log-log-convex data

Log-sum-exp neural networks and posynomial models for convex and log-log-convex data

20 June 2018
M. Akian
S. Gaubert
Jérémie Guillaud
ArXivPDFHTML

Papers citing "Log-sum-exp neural networks and posynomial models for convex and log-log-convex data"

4 / 4 papers shown
Title
SPINE: Soft Piecewise Interpretable Neural Equations
SPINE: Soft Piecewise Interpretable Neural Equations
Jasdeep Singh Grover
Harsh Minesh Domadia
Rajashree Tapase
Grishma Sharma
21
0
0
20 Nov 2021
Polyconvex anisotropic hyperelasticity with neural networks
Polyconvex anisotropic hyperelasticity with neural networks
Dominik K. Klein
Mauricio Fernández
Robert J. Martin
P. Neff
Oliver Weeger
41
151
0
20 Jun 2021
Advances in the training, pruning and enforcement of shape constraints
  of Morphological Neural Networks using Tropical Algebra
Advances in the training, pruning and enforcement of shape constraints of Morphological Neural Networks using Tropical Algebra
Nikolaos Dimitriadis
Petros Maragos
16
9
0
15 Nov 2020
A Universal Approximation Result for Difference of log-sum-exp Neural
  Networks
A Universal Approximation Result for Difference of log-sum-exp Neural Networks
G. Calafiore
S. Gaubert
Member
C. Possieri
19
44
0
21 May 2019
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