Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Density Estimation and Likelihood-free Inference   I consider two problems in machine learning and statistics: the problem of
estimating the joint probability density of a collection of random variables,
known as density estimation, and the problem of inferring model parameters when
their likelihood is intractable, known as likelihood-free inference. The
contribution of the thesis is a set of new methods for addressing these
problems that are based on recent advances in neural networks and deep
learning.

37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys