This report summarizes the second International Verification of Neural Networks
Competition (VNN-COMP 2021), held as a part of the 4th Workshop on Formal Methods for …

This report summarizes the 3rd International Verification of Neural Networks Competition
(VNN-COMP 2022), held as a part of the 5th Workshop on Formal Methods for ML-Enabled …

Deep neural networks are increasingly being used as controllers for safety-critical systems.
Because neural networks are opaque, certifying their correctness is a significant challenge …

With the rapid growth of machine learning, deep neural networks (DNNs) are now being
used in numerous domains. Unfortunately, DNNs are “black-boxes”, and cannot be …

The application of deep reinforcement learning (DRL) to computer and networked systems
has recently gained significant popularity. However, the obscurity of decisions by DRL …

This report summarizes the 4th International Verification of Neural Networks Competition
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …

Deep learning methods can be used to produce control policies, but certifying their safety is
challenging. The resulting networks are nonlinear and often very large. In response to this …

Deep learning has emerged as an effective approach for creating modern software systems,
with neural networks often surpassing hand-crafted systems. Unfortunately, neural networks …

Deep neural networks have emerged as a widely used and effective means for tackling
complex, real-world problems. However, a major obstacle in applying them to safety-critical …

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