Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computing Inferences for Large-Scale Continuous-Time Markov Chains by
  Combining Lumping with Imprecision   If the state space of a homogeneous continuous-time Markov chain is too
large, making inferences - here limited to determining marginal or limit
expectations - becomes computationally infeasible. Fortunately, the state space
of such a chain is usually too detailed for the inferences we are interested
in, in the sense that a less detailed - smaller - state space suffices to
unambiguously formalise the inference. However, in general this so-called
lumped state space inhibits computing exact inferences because the
corresponding dynamics are unknown and/or intractable to obtain. We address
this issue by considering an imprecise continuous-time Markov chain. In this
way, we are able to provide guaranteed lower and upper bounds for the
inferences of interest, without suffering from the curse of dimensionality.

20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph