Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dynamic Bayesian Network Auxiliary ABC-SMC for Hybrid Model Bayesian
  Inference to Accelerate Biomanufacturing Process Mechanism Learning and
  Robust Control   Driven by the critical needs of biomanufacturing 4.0, we present a
probabilistic knowledge graph hybrid model characterizing complex
spatial-temporal causal interdependencies of underlying bioprocessing
mechanisms. It can faithfully capture the important properties, including
nonlinear reactions, partially observed state, and nonstationary dynamics.
Given limited process observations, we derive a posterior distribution
quantifying model uncertainty, which can facilitate mechanism learning and
support robust process control. To avoid evaluation of intractable likelihood,
Approximate Bayesian Computation sampling with Sequential Monte Carlo (ABC-SMC)
is developed to approximate the posterior distribution. Given high stochastic
and model uncertainties, it is computationally expensive to match process
output trajectories. Therefore, we propose a linear Gaussian dynamic Bayesian
network (LG-DBN) auxiliary likelihood-based ABC-SMC algorithm. Through matching
observed and simulated summary statistics, the proposed approach can
dramatically reduce the computation cost and accelerate the posterior
approximation convergence.

22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom