Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural ODEs for Informative Missingness in Multivariate Time Series   Informative missingness is unavoidable in the digital processing of
continuous time series, where the value for one or more observations at
different time points are missing. Such missing observations are one of the
major limitations of time series processing using deep learning. Practical
applications, e.g., sensor data, healthcare, weather, generates data that is in
truth continuous in time, and informative missingness is a common phenomenon in
these datasets. These datasets often consist of multiple variables, and often
there are missing values for one or many of these variables. This
characteristic makes time series prediction more challenging, and the impact of
missing input observations on the accuracy of the final output can be
significant. A recent novel deep learning model called GRU-D is one early
attempt to address informative missingness in time series data. On the other
hand, a new family of neural networks called Neural ODEs (Ordinary Differential
Equations) are natural and efficient for processing time series data which is
continuous in time. In this paper, a deep learning model is proposed that
leverages the effective imputation of GRU-D, and the temporal continuity of
Neural ODEs. A time series classification task performed on the PhysioNet
dataset demonstrates the performance of this architecture.

13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
3
The categories of this paper are: physics
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom