Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stochastic Neural Networks with Infinite Width are Deterministic   This work theoretically studies stochastic neural networks, a main type of
neural network in use. Specifically, we prove that as the width of an optimized
stochastic neural network tends to infinity, its predictive variance on the
training set decreases to zero. Two common examples that our theory applies to
are neural networks with dropout and variational autoencoders. Our result helps
better understand how stochasticity affects the learning of neural networks and
thus design better architectures for practical problems.

14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom