Search Results for author: Christopher Hahn

Found 6 papers, 4 papers with code

Generating Symbolic Reasoning Problems with Transformer GANs

1 code implementation19 Oct 2021 Jens U. Kreber, Christopher Hahn

Constructing training data for symbolic reasoning domains is challenging: Existing instances are typically hand-crafted and too few to be trained on directly and synthetically generated instances are often hard to evaluate in terms of their meaningfulness.

Neural Circuit Synthesis from Specification Patterns

1 code implementation NeurIPS 2021 Frederik Schmitt, Christopher Hahn, Markus N. Rabe, Bernd Finkbeiner

We train hierarchical Transformers on the task of synthesizing hardware circuits directly out of high-level logical specifications in linear-time temporal logic (LTL).

Efficient Monitoring of Hyperproperties using Prefix Trees

no code implementations18 Jan 2021 Bernd Finkbeiner, Christopher Hahn, Marvin Stenger, Leander Tentrup

Hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other and are thus not monitorable by tools that consider computations in isolation.

Logic in Computer Science

Realizing Omega-regular Hyperproperties

no code implementations18 Jan 2021 Bernd Finkbeiner, Christopher Hahn, Jana Hofmann, Leander Tentrup

We furthermore studied the realizability problem of HyperQPTL.

Logic in Computer Science

Teaching Temporal Logics to Neural Networks

1 code implementation ICLR 2021 Christopher Hahn, Frederik Schmitt, Jens U. Kreber, Markus N. Rabe, Bernd Finkbeiner

We study two fundamental questions in neuro-symbolic computing: can deep learning tackle challenging problems in logics end-to-end, and can neural networks learn the semantics of logics.

Constraint-Based Monitoring of Hyperproperties

4 code implementations31 May 2019 Christopher Hahn, Marvin Stenger, Leander Tentrup

Verifying hyperproperties at runtime is a challenging problem as hyperproperties, such as non-interference and observational determinism, relate multiple computation traces with each other.

Logic in Computer Science

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