PiShield: A PyTorch Package for Learning with Requirements
arxiv(2024)
摘要
Deep learning models have shown their strengths in various application
domains, however, they often struggle to meet safety requirements for their
outputs. In this paper, we introduce PiShield, the first package ever allowing
for the integration of the requirements into the neural networks' topology.
PiShield guarantees compliance with these requirements, regardless of input.
Additionally, it allows for integrating requirements both at inference and/or
training time, depending on the practitioners' needs. Given the widespread
application of deep learning, there is a growing need for frameworks allowing
for the integration of the requirements across various domains. Here, we
explore three application scenarios: functional genomics, autonomous driving,
and tabular data generation.
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