As robustness verification methods are becoming more precise, training
c...
Training certifiably robust neural networks remains a notoriously hard
p...
Neural Ordinary Differential Equations (NODEs) are a novel neural
archit...
This paper presents a summary and meta-analysis of the first three itera...
This report summarizes the 3rd International Verification of Neural Netw...
We propose the novel certified training method, SABR, which outperforms
...
Tree-based models are used in many high-stakes application domains such ...
State-of-the-art neural network verifiers are fundamentally based on one...
Randomized Smoothing (RS) is considered the state-of-the-art approach to...
Monotone Operator Equilibrium Models (monDEQs) represent a class of mode...
Randomized Smoothing (RS) is a promising method for obtaining robustness...
Formal verification of neural networks is critical for their safe adopti...