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pro vyhledávání: '"Detlefsen, Nicki Skafte"'
Autor:
Hauschultz, Helene, Moreno-Muños, Rasmus Berg Palm. Pablo, Detlefsen, Nicki Skafte, Plessis, Andrew Allan du, Hauberg, Søren
The encoder network of an autoencoder is an approximation of the nearest point projection onto the manifold spanned by the decoder. A concern with this approximation is that, while the output of the encoder is always unique, the projection can possib
Externí odkaz:
http://arxiv.org/abs/2206.01552
Publikováno v:
Nature Communications 13, 1914 (2022)
How we choose to represent our data has a fundamental impact on our ability to subsequently extract information from them. Machine learning promises to automatically determine efficient representations from large unstructured datasets, such as those
Externí odkaz:
http://arxiv.org/abs/2012.02679
Disentangled representation learning finds compact, independent and easy-to-interpret factors of the data. Learning such has been shown to require an inductive bias, which we explicitly encode in a generative model of images. Specifically, we propose
Externí odkaz:
http://arxiv.org/abs/1906.11881
Akademický článek
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Autor:
Detlefsen, Nicki Skafte
Publikováno v:
Detlefsen, N S 2020, Learning invariant representations from prior knowledge in Deep Learning . Technical University of Denmark .
This thesis consist of 5 independent pieces of work divided over 4 chapters. This manuscript tries to bind them together under one common theme: how priorknowledge can be used to incorporate inductive biases into deep learning models. The first chapt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1202::36421abfe3834ffef8e415f3940aa2c9
https://orbit.dtu.dk/en/publications/5b7f737a-b2a0-4e3f-91ff-027533c8ca53
https://orbit.dtu.dk/en/publications/5b7f737a-b2a0-4e3f-91ff-027533c8ca53