19 citations · 31 across the 15 of their papers we have counts for
3 papers · 1 filter
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Edoardo Manino, Iury Bessa, Lucas Cordeiro
Neural networks are a powerful class of non-linear functions. However, their black-box nature makes it difficult to explain their behaviour and certify their safety. Abstraction te…
CEG4N: Counter-Example Guided Neural Network Quantization Refinement
João Batista P. Matos, Iury Bessa, Edoardo Manino +2
Neural networks are essential components of learning-based software systems. However, their high compute, memory, and power requirements make using them in low resources domains ch…
Verifying Quantized Neural Networks using SMT-Based Model Checking
Luiz Sena, Xidan Song, Erickson Alves +4
Artificial Neural Networks (ANNs) are being deployed for an increasing number of safety-critical applications, including autonomous cars and medical diagnosis. However, concerns ab…