Dec 21, 2020 · This paper describes the first bit-precise symbolic verification framework to reason over actual implementations of ANNs in CUDA, based on ...

Sep 13, 2024 · This paper describes the first bit-precise symbolic verification framework to reason over actual implementations of ANNs in CUDA, based on invariant inference.

Dec 21, 2020 · In this paper we focus on specific networks known as Multi-Layer Perceptrons (MLPs), and we propose a solution to verify their safety using ...

Complete verification of deep neural networks (DNNs) can exactly determine whether the DNN satisfies a desired trustworthy property (e.g., robustness, ...

Verifier runs through the unittest framework. A new unit test can be added to run the verifier with a specific configuration. Current unit tests are located ...

Jul 16, 2024 · Offline handwritten signature verification is one of the most prevalent and prominent biometric methods in many application fields.

Missing: Point Implementations

In this section, we discuss how our implementation models work to support fixed-point verification of neural network implementations. There exist two ways ...

We present an intuitive yet comprehensive syntax of the fixed-point theory, and provide formal semantics for it based on rational arithmetic.

QNNVerifier is the first open-source tool for verifying implementations of neural networks that takes into account the finite word-length (i.e. ...