Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Importance of Balanced Data Sets: Analyzing a Vehicle Trajectory
  Prediction Model based on Neural Networks and Distributed Representations   Predicting future behavior of other traffic participants is an essential task
that needs to be solved by automated vehicles and human drivers alike to
achieve safe and situationaware driving. Modern approaches to vehicles
trajectory prediction typically rely on data-driven models like neural
networks, in particular LSTMs (Long Short-Term Memorys), achieving promising
results. However, the question of optimal composition of the underlying
training data has received less attention. In this paper, we expand on previous
work on vehicle trajectory prediction based on neural network models employing
distributed representations to encode automotive scenes in a semantic vector
substrate. We analyze the influence of variations in the training data on the
performance of our prediction models. Thereby, we show that the models
employing our semantic vector representation outperform the numerical model
when trained on an adequate data set and thereby, that the composition of
training data in vehicle trajectory prediction is crucial for successful
training. We conduct our analysis on challenging real-world driving data.

16
The categories of this paper are: stat
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
19
The categories of this paper are: eess
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn