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- Matthew L. Daggitt
The University of Western Australia, Perth, Australia
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Publication search results
found 32 matches
- 2024
- Matthew L. Daggitt, Timothy G. Griffin:
Formally Verified Convergence of Policy-Rich DBF Routing Protocols. IEEE/ACM Trans. Netw. 32(2): 1645-1660 (2024) - Matthew L. Daggitt, Wen Kokke, Robert Atkey, Natalia Slusarz, Luca Arnaboldi, Ekaterina Komendantskaya:
Vehicle: Bridging the Embedding Gap in the Verification of Neuro-Symbolic Programs. CoRR abs/2401.06379 (2024) - 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:
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. CoRR abs/2401.14461 (2024) - Matthew L. Daggitt, Wen Kokke, Robert Atkey:
Efficient compilation of expressive problem space specifications to neural network solvers. CoRR abs/2402.01353 (2024) - Marco Casadio, Tanvi Dinkar, Ekaterina Komendantskaya, Luca Arnaboldi, Omri Isac, Matthew L. Daggitt, Guy Katz, Verena Rieser, Oliver Lemon:
NLP Verification: Towards a General Methodology for Certifying Robustness. CoRR abs/2403.10144 (2024) - 2023
- Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya:
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. FoMLAS@CAV 2023: 59-70 - Matthew L. Daggitt, Wen Kokke, Ekaterina Komendantskaya, Robert Atkey, Luca Arnaboldi, Natalia Slusarz, Marco Casadio, Ben Coke, Jeonghyeon Lee:
The Vehicle Tutorial: Neural Network Verification with Vehicle. FoMLAS@CAV 2023: 1-5 - Matthew L. Daggitt, Robert Atkey, Wen Kokke, Ekaterina Komendantskaya, Luca Arnaboldi:
Compiling Higher-Order Specifications to SMT Solvers: How to Deal with Rejection Constructively. CPP 2023: 102-120 - Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark:
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. LPAR 2023: 473-493 - Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart, Kathrin Stark:
Logic of Differentiable Logics: Towards a Uniform Semantics of DL. CoRR abs/2303.10650 (2023) - Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac, Tanvi Dinkar, Daniel Kienitz, Verena Rieser, Ekaterina Komendantskaya:
ANTONIO: Towards a Systematic Method of Generating NLP Benchmarks for Verification. CoRR abs/2305.04003 (2023) - 2022
- Ruby C. Marsden, Christopher L. Kirkland, Martin Danisík, Matthew L. Daggitt, Ung-San Ahn, Bjarne Friedrichs, Noreen J. Evans:
A new approach to SHRIMP II zircon U-Th disequilibrium dating. Comput. Geosci. 158: 104947 (2022) - Taryn Scharf, Christopher L. Kirkland, Matthew L. Daggitt, Milo Barham, Vladimir Puzyrev:
AnalyZr: A Python application for zircon grain image segmentation and shape analysis. Comput. Geosci. 162: 105057 (2022) - Matthew L. Daggitt, Timothy G. Griffin:
Dynamic asynchronous iterations. J. Parallel Distributed Comput. 164: 168-177 (2022) - Marco Casadio, Ekaterina Komendantskaya, Matthew L. Daggitt, Wen Kokke, Guy Katz, Guy Amir, Idan Refaeli:
Neural Network Robustness as a Verification Property: A Principled Case Study. CAV (1) 2022: 219-231 - Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart:
Differentiable Logics for Neural Network Training and Verification. NSV/FoMLAS@CAV 2022: 67-77 - Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya, Matthew L. Daggitt:
CheckINN: Wide Range Neural Network Verification in Imandra. PPDP 2022: 3:1-3:14 - Matthew L. Daggitt, Wen Kokke, Robert Atkey, Luca Arnaboldi, Ekaterina Komendantskaya:
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers. CoRR abs/2202.05207 (2022) - Marco Casadio, Ekaterina Komendantskaya, Verena Rieser, Matthew L. Daggitt, Daniel Kienitz, Luca Arnaboldi, Wen Kokke:
Why Robust Natural Language Understanding is a Challenge. CoRR abs/2206.14575 (2022) - Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart:
Differentiable Logics for Neural Network Training and Verification. CoRR abs/2207.06741 (2022) - Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya, Matthew L. Daggitt:
CheckINN: Wide Range Neural Network Verification in Imandra (Extended). CoRR abs/2207.10562 (2022) - 2021
- Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick:
Actions you can handle: dependent types for AI plans. TyDe@ICFP 2021: 1-13 - Marco Casadio, Matthew L. Daggitt, Ekaterina Komendantskaya, Wen Kokke, Daniel Kienitz, Rob Stewart:
Property-driven Training: All You (N)Ever Wanted to Know About. CoRR abs/2104.01396 (2021) - Alasdair Hill, Ekaterina Komendantskaya, Matthew L. Daggitt, Ronald P. A. Petrick:
Actions You Can Handle: Dependent Types for AI Plans. CoRR abs/2105.11267 (2021) - Matthew L. Daggitt, Timothy G. Griffin:
Formally Verified Convergence of Policy-Rich DBF Routing Protocols. CoRR abs/2106.01184 (2021) - 2020
- Matthew L. Daggitt, Ran Zmigrod, Timothy G. Griffin:
A Relaxation of Üresin and Dubois' Asynchronous Fixed-Point Theory in Agda. J. Autom. Reason. 64(5): 857-877 (2020) - Matthew L. Daggitt, Timothy G. Griffin:
Dynamic Asynchronous Iterations. CoRR abs/2012.01686 (2020) - 2019
- Matthew L. Daggitt:
An algebraic perspective on the convergence of vector-based routing protocols. University of Cambridge, UK, 2019 - 2018
- Matthew L. Daggitt, Timothy G. Griffin:
Rate of Convergence of Increasing Path-Vector Routing Protocols. ICNP 2018: 335-345 - Ran Zmigrod, Matthew L. Daggitt, Timothy G. Griffin:
An Agda Formalization of Üresin and Dubois' Asynchronous Fixed-Point Theory. ITP 2018: 623-639
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