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Dimitri Lozeve 2020-04-14 12:51:55 +02:00
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posts/hierarchical-optimal-transport-for-document-classification.org
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@ -154,8 +154,12 @@ to a deep learning approach, we can make sense of every intermediate
step, from the representations of topics to the weights in the
optimisation algorithm to compute higher-level distances.
#+caption: Representation of two documents in topic space, along with how the distance was computed between them. Everything is interpretable: from the documents as collections of topics, to the matchings between topics determining the overall distance between the books citep:yurochkin2019_hierar_optim_trans_docum_repres.
[[file:/images/hott_fig1.jpg]]
[fn::{-} Representation of two documents in topic space, along with
how the distance was computed between them. Everything is
interpretable: from the documents as collections of topics, to the
matchings between topics determining the overall distance between the
books citep:yurochkin2019_hierar_optim_trans_docum_repres.]
* Experiments