119 citations · 465 across the 38 of their papers we have counts for
4 papers · 1 filter
Scalable Verification of GNN-based Job Schedulers
Haoze Wu, Clark Barrett, Mahmood Sharif +2
Recently, Graph Neural Networks (GNNs) have been applied for scheduling jobs over clusters, achieving better performance than hand-crafted heuristics. Despite their impressive perf…
Verifying Recurrent Neural Networks using Invariant Inference
Yuval Jacoby, Clark Barrett, Guy Katz
Deep neural networks are revolutionizing the way complex systems are developed. However, these automatically-generated networks are opaque to humans, making it difficult to reason…
Toward Scalable Verification for Safety-Critical Deep Networks
Lindsey Kuper, Guy Katz, Justin Gottschlich +3
The increasing use of deep neural networks for safety-critical applications, such as autonomous driving and flight control, raises concerns about their safety and reliability. Form…
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz, Clark Barrett, David Dill +2
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 syst…