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Found 9 papers, 5 papers with code
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
This paper serves as a comprehensive system description of version 2. 0 of the Marabou framework for formal analysis of neural networks.
Efficient compilation of expressive problem space specifications to neural network solvers
Recent work has described the presence of the embedding gap in neural network verification.
Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs
Neuro-symbolic programs -- programs containing both machine learning components and traditional symbolic code -- are becoming increasingly widespread.
Why Robust Natural Language Understanding is a Challenge
With the proliferation of Deep Machine Learning into real-life applications, a particular property of this technology has been brought to attention: robustness Neural Networks notoriously present low robustness and can be highly sensitive to small input perturbations.
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers
However, although work has managed to incorporate the results of these verifiers to prove larger properties of individual systems, there is currently no general methodology for bridging the gap between verifiers and interactive theorem provers (ITPs).
Network robustness as a mathematical property: training, evaluation and attack
We also perform experiments to compare the applicability and efficacy of different training methods for ensuring the network obeys these different definitions.
Neural Network Robustness as a Verification Property: A Principled Case Study
Neural networks are very successful at detecting patterns in noisy data, and have become the technology of choice in many fields.
Featherweight Go
We describe a design for generics in Go inspired by previous work on Featherweight Java by Igarashi, Pierce, and Wadler.
Programming Languages Logic in Computer Science
Formalising Type-Logical Grammars in Agda
And finally, we will put our system to use in the analysis of a simple example sentence.
