Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reachability Analysis for Feed-Forward Neural Networks using Face
  Lattices   Deep neural networks have been widely applied as an effective approach to
handle complex and practical problems. However, one of the most fundamental
open problems is the lack of formal methods to analyze the safety of their
behaviors. To address this challenge, we propose a parallelizable technique to
compute exact reachable sets of a neural network to an input set. Our method
currently focuses on feed-forward neural networks with ReLU activation
functions. One of the primary challenges for polytope-based approaches is
identifying the intersection between intermediate polytopes and hyperplanes
from neurons. In this regard, we present a new approach to construct the
polytopes with the face lattice, a complete combinatorial structure. The
correctness and performance of our methodology are evaluated by verifying the
safety of ACAS Xu networks and other benchmarks. Compared to state-of-the-art
methods such as Reluplex, Marabou, and NNV, our approach exhibits a
significantly higher efficiency. Additionally, our approach is capable of
constructing the complete input set given an output set, so that any input that
leads to safety violation can be tracked.

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The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
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The categories of this paper are: econ
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The categories of this paper are: astro-ph
2
The categories of this paper are: math
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The categories of this paper are: alg-geom