Matthew L. Daggitt

According to our database, Matthew L. Daggitt authored at least 26 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Formally Verified Convergence of Policy-Rich DBF Routing Protocols.

Matthew L. Daggitt, Timothy G. Griffin

IEEE/ACM Trans. Netw., April, 2024

NLP Verification: Towards a General Methodology for Certifying Robustness.

Marco Casadio, Tanvi Dinkar, Ekaterina Komendantskaya, Luca Arnaboldi, Omri Isac, Matthew L. Daggitt, Guy Katz, Verena Rieser, Oliver Lemon

CoRR, 2024

Efficient compilation of expressive problem space specifications to neural network solvers.

Matthew L. Daggitt, Wen Kokke, Robert Atkey

CoRR, 2024

Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs.

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Natalia Slusarz, Luca Arnaboldi, Ekaterina Komendantskaya

CoRR, 2024

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks.

Haoze Wu, Omri Isac, Aleksandar Zeljic, Teruhiro Tagomori, Matthew L. Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark W. Barrett

Proceedings of the Computer Aided Verification - 36th International Conference, 2024

2023

Logic of Differentiable Logics: Towards a Uniform Semantics of DL.

Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark

Proceedings of the LPAR 2023: Proceedings of 24th International Conference on Logic for Programming, 2023

Compiling Higher-Order Specifications to SMT Solvers: How to Deal with Rejection Constructively.

Matthew L. Daggitt, Robert Atkey, Wen Kokke, Ekaterina Komendantskaya, Luca Arnaboldi

Proceedings of the 12th ACM SIGPLAN International Conference on Certified Programs and Proofs, 2023

The Vehicle Tutorial: Neural Network Verification with Vehicle.

Matthew L. Daggitt, Wen Kokke, Ekaterina Komendantskaya, Robert Atkey, Luca Arnaboldi, Natalia Slusarz, Marco Casadio, Ben Coke, Jeonghyeon Lee

Proceedings of the 6th Workshop on Formal Methods for ML-Enabled Autonomous Systems, 2023

ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification.

Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya

Proceedings of the 6th Workshop on Formal Methods for ML-Enabled Autonomous Systems, 2023

2022

Dynamic asynchronous iterations.

Matthew L. Daggitt, Timothy G. Griffin

J. Parallel Distributed Comput., 2022

AnalyZr: A Python application for zircon grain image segmentation and shape analysis.

Taryn Scharf, Christopher L. Kirkland, Matthew L. Daggitt, Milo Barham, Vladimir Puzyrev

Comput. Geosci., 2022

A new approach to SHRIMP II zircon U-Th disequilibrium dating.

Ruby C. Marsden, Christopher L. Kirkland, Martin Danisík, Matthew L. Daggitt, Ung-San Ahn, Bjarne Friedrichs, Noreen J. Evans

Comput. Geosci., 2022

CheckINN: Wide Range Neural Network Verification in Imandra (Extended).

Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya, Matthew L. Daggitt

CoRR, 2022

Why Robust Natural Language Understanding is a Challenge.

Marco Casadio, Ekaterina Komendantskaya, Verena Rieser, Matthew L. Daggitt, Daniel Kienitz, Luca Arnaboldi, Wen Kokke

CoRR, 2022

Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers.

Matthew L. Daggitt, Wen Kokke, Robert Atkey, Luca Arnaboldi, Ekaterina Komendantskaya

CoRR, 2022

CheckINN: Wide Range Neural Network Verification in Imandra.

Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya, Matthew L. Daggitt

Proceedings of the PPDP 2022: 24th International Symposium on Principles and Practice of Declarative Programming, Tbilisi, Georgia, September 20, 2022

Differentiable Logics for Neural Network Training and Verification.

Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart

Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022

Neural Network Robustness as a Verification Property: A Principled Case Study.

Marco Casadio, Ekaterina Komendantskaya, Matthew L. Daggitt, Wen Kokke, Guy Katz, Guy Amir, Idan Refaeli

Proceedings of the Computer Aided Verification - 34th International Conference, 2022

2021

Property-driven Training: All You (N)Ever Wanted to Know About.

Marco Casadio, Matthew L. Daggitt, Ekaterina Komendantskaya, Wen Kokke, Daniel Kienitz, Rob Stewart

CoRR, 2021

Actions you can handle: dependent types for AI plans.

Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick

Proceedings of the TyDe 2021: Proceedings of the 6th ACM SIGPLAN International Workshop on Type-Driven Development, 2021

2020

A Relaxation of Üresin and Dubois' Asynchronous Fixed-Point Theory in Agda.

Matthew L. Daggitt, Ran Zmigrod, Timothy G. Griffin

J. Autom. Reason., 2020

2019

An algebraic perspective on the convergence of vector-based routing protocols

Matthew L. Daggitt

PhD thesis, 2019

2018

Asynchronous convergence of policy-rich distributed bellman-ford routing protocols.

Matthew L. Daggitt, Alexander J. T. Gurney, Timothy G. Griffin

Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication, 2018

An Agda Formalization of Üresin and Dubois' Asynchronous Fixed-Point Theory.

Ran Zmigrod, Matthew L. Daggitt, Timothy G. Griffin

Proceedings of the Interactive Theorem Proving - 9th International Conference, 2018

Rate of Convergence of Increasing Path-Vector Routing Protocols.

Matthew L. Daggitt, Timothy G. Griffin

Proceedings of the 2018 IEEE 26th International Conference on Network Protocols, 2018

2015

Tracking Urban Activity Growth Globally with Big Location Data.

Matthew L. Daggitt, Anastasios Noulas, Blake Shaw, Cecilia Mascolo

CoRR, 2015