Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: McTorch, a manifold optimization library for deep learning   In this paper, we introduce McTorch, a manifold optimization library for deep
learning that extends PyTorch. It aims to lower the barrier for users wishing
to use manifold constraints in deep learning applications, i.e., when the
parameters are constrained to lie on a manifold. Such constraints include the
popular orthogonality and rank constraints, and have been recently used in a
number of applications in deep learning. McTorch follows PyTorch's architecture
and decouples manifold definitions and optimizers, i.e., once a new manifold is
added it can be used with any existing optimizer and vice-versa. McTorch is
available at https://github.com/mctorch .

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The categories of this paper are: cond-mat
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: q-bio
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-th
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: solv-int
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The categories of this paper are: math-ph
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The categories of this paper are: adap-org
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The categories of this paper are: mtrl-th