Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On the Relationship Between Probabilistic Circuits and Determinantal
  Point Processes   Scaling probabilistic models to large realistic problems and datasets is a
key challenge in machine learning. Central to this effort is the development of
tractable probabilistic models (TPMs): models whose structure guarantees
efficient probabilistic inference algorithms. The current landscape of TPMs is
fragmented: there exist various kinds of TPMs with different strengths and
weaknesses. Two of the most prominent classes of TPMs are determinantal point
processes (DPPs) and probabilistic circuits (PCs). This paper provides the
first systematic study of their relationship. We propose a unified analysis and
shared language for discussing DPPs and PCs. Then we establish theoretical
barriers for the unification of these two families, and prove that there are
cases where DPPs have no compact representation as a class of PCs. We close
with a perspective on the central problem of unifying these tractable models.

37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math