Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Causal-based Framework for Multimodal Multivariate Time Series
  Validation Enhanced by Unsupervised Deep Learning as an Enabler for Industry
  4.0   An advanced conceptual validation framework for multimodal multivariate time
series defines a multi-level contextual anomaly detection ranging from an
univariate context definition, to a multimodal abstract context representation
learnt by an Autoencoder from heterogeneous data (images, time series, sounds,
etc.) associated to an industrial process. Each level of the framework is
either applicable to historical data and/or live data. The ultimate level is
based on causal discovery to identify causal relations in observational data in
order to exclude biased data to train machine learning models and provide means
to the domain expert to discover unknown causal relations in the underlying
process represented by the data sample. A Long Short-Term Memory Autoencoder is
successfully evaluated on multivariate time series to validate the learnt
representation of abstract contexts associated to multiple assets of a blast
furnace. A research roadmap is identified to combine causal discovery and
representation learning as an enabler for unsupervised Root Cause Analysis
applied to the process industry.

31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math