46 citations · 64 across the 17 of their papers we have counts for
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cs.LG2020★ 3 cited
Certifying Neural Network Robustness to Random Input Noise from Samples
Brendon G. Anderson, Somayeh Sojoudi
Methods to certify the robustness of neural networks in the presence of input uncertainty are vital in safety-critical settings. Most certification methods in the literature are de…
cs.LG2020
Data-Driven Certification of Neural Networks with Random Input Noise
Brendon G. Anderson, Somayeh Sojoudi
Methods to certify the robustness of neural networks in the presence of input uncertainty are vital in safety-critical settings. Most certification methods in the literature are de…
cs.LG2020
Tightened Convex Relaxations for Neural Network Robustness Certification
Brendon G. Anderson, Ziye Ma, Jingqi Li +1
In this paper, we consider the problem of certifying the robustness of neural networks to perturbed and adversarial input data. Such certification is imperative for the application…