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In implicit models, one often interpolates between sampled points in latent space.
Maximum likelihood estimation and factor analysis
Gale Young · 1941
Earlier work this paper cites.
Animating rotation with quaternion curves
Ken Shoemake · 1985
Earlier work this paper cites.
Latent Variable Models and Factor Analysis
D. J. Bartholomew · 1987
Earlier work this paper cites.
Neural networks and principal component analysis: Learning from examples without local minima
Pierre Baldi and Kurt Hornik · 1989
Earlier work this paper cites.
n–linear dimensionality reduction
David DeMers and GW Cottrell · 1993
Earlier work this paper cites.
Bayesian neural networks and density networks
David JC MacKay · 1995
Earlier work this paper cites.
Foundations of modern probability
Olav Kallenberg · 2006
Cited alongside, same era.
Auto-Encoding Variational Bayes
Diederik P Kingma and Max Welling · 2013
Cited alongside, same era.
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Towards principled methods for training generative adversarial networks
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Optimizing the latent space of generative networks
Piotr Bojanowski, Armand Joulin, David Lopez-Paz, and Arthur Szlam · 2017
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Semantically decomposing the latent spaces of generative adversarial networks
Chris Donahue, Akshay Balsubramani, Julian McAuley, and Zachary C Lipton · 2017
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