Web Reference: Jul 6, 2020 · This paper proposes a new type of generative model that is able to quickly learn a latent representation without an encoder. Neural networks for implicit representations, such as SIRENs, have been very successful at modeling natural signals. However, in the classical approach, each data point requires its own neural ... By initialising a latent vector of our unknown parameters with zeros, we have shown that it is possible to compute the gradients of the data fitting loss with respect to this origin, and then jointly fit the data while learning this new point of reference in the latent space.
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