• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 345 matches

• 2023
• 
  Farid Arfi, Anne-Lise Courbis, Thomas Lambolais, François Bughin, Maurice Hayot:
  Formal verification of a telerehabilitation system through an abstraction and refinement approach using Uppaal. IET Softw. 17(4): 582-599 (2023)
• 
  Raphael Kreft, Clemens Büchner, Silvan Sievers, Malte Helmert:
  Computing Domain Abstractions for Optimal Classical Planning with Counterexample-Guided Abstraction Refinement. ICAPS 2023: 221-226
• 
  Richard Banach, John W. Baugh Jr.:
  Formalisation, Abstraction and Refinement of Bond Graphs. ICGT 2023: 145-162
• 
  Tobias Ladner, Matthias Althoff:
  Automatic Abstraction Refinement in Neural Network Verification using Sensitivity Analysis. HSCC 2023: 18:1-18:13
• 
  Carsten Lutz, Lukas Schulze:
  Description Logics with Abstraction and Refinement. KR 2023: 492-501
• 
  Sebastian Stock, Fabian Vu, David Geleßus, Michael Leuschel, Atif Mashkoor, Alexander Egyed:
  Validation by Abstraction and Refinement. ABZ 2023: 160-178
• 
  Pavel Surynek:
  Counterexample Guided Abstraction Refinement with Non-Refined Abstractions for Multi-Agent Path Finding. CoRR abs/2301.08687 (2023)
• 
  Adrien Banse, Licio Romao, Alessandro Abate, Raphaël M. Jungers:
  Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]. CoRR abs/2303.17618 (2023)
• 
  Carsten Lutz, Lukas Schulze:
  Description Logics with Abstraction and Refinement. CoRR abs/2306.03717 (2023)
• 
  Calvin Chau, Jan Kretínský, Stefanie Mohr:
  Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks. CoRR abs/2307.10891 (2023)
• 2022
• 
  David Speck, Jendrik Seipp:
  New Refinement Strategies for Cartesian Abstractions. ICAPS 2022: 348-352
• 
  Matan Ostrovsky, Clark W. Barrett, Guy Katz:
  An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks. ATVA 2022: 391-396
• 
  Sebastian Junges, Matthijs T. J. Spaan:
  Abstraction-Refinement for Hierarchical Probabilistic Models. CAV (1) 2022: 102-123
• 
  Haowei Liang, Chunyan Hou, Jinsong Wang, Chen Chen:
  An Extention of Lazy Abstraction and Refinement for Program Verification. COMPSAC 2022: 1750-1755
• 
  Simone Smeraldo, Riccardo Desimini, Maria Prandini:
  An abstraction and refinement computational approach to safety verification of discrete time nonlinear systems. ECC 2022: 572-579
• 
  Benedikt Maderbacher, Roderick Bloem:
  Reactive Synthesis Modulo Theories using Abstraction Refinement. FMCAD 2022: 315-324
• 
  Aleksandar S. Dimovski:
  Model sketching by abstraction refinement for lifted model checking. SAC 2022: 1845-1848
• 
  Matan Ostrovsky, Clark W. Barrett, Guy Katz:
  An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks. CoRR abs/2201.01978 (2022)
• 
  Sebastian Junges, Matthijs T. J. Spaan:
  Abstraction-Refinement for Hierarchical Probabilistic Models. CoRR abs/2206.02653 (2022)
• 
  Jiaxiang Liu, Yunhan Xing, Xiaomu Shi, Fu Song, Zhiwu Xu, Zhong Ming:
  Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks. CoRR abs/2207.00759 (2022)
• 
  Mohamed Toufik Ailane, Christoph Knieke, Andreas Rausch:
  How to Extend the Abstraction Refinement Model for Systems with Emergent Behavior ? CoRR abs/2208.13471 (2022)
• 2021
• 
  Tamás Tóth:
  Abstraction Refinement-Based Verification of Timed Automata. Budapest University of Technology and Economics, Hungary, 2021
• 
  Franck Cassez, Peter Gjøl Jensen, Kim Guldstrand Larsen:
  Verification and Parameter Synthesis for Real-Time Programs using Refinement of Trace Abstraction. Fundam. Informaticae 178(1-2): 31-57 (2021)
• 
  Maxence Dutreix, Samuel Coogan:
  Specification-Guided Verification and Abstraction Refinement of Mixed Monotone Stochastic Systems. IEEE Trans. Autom. Control. 66(7): 2975-2990 (2021)
• 
  Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jégourel:
  Automatically 'Verifying' Discrete-Time Complex Systems through Learning, Abstraction and Refinement. IEEE Trans. Software Eng. 47(1): 189-203 (2021)
• 
  Wael Fatnassi, Yasser Shoukry:
  PolyAR: A Highly Parallelizable Solver For Polynomial Inequality Constraints Using Convex Abstraction Refinement. ADHS 2021: 43-48
• 
  Stanley Bak:
  nnenum: Verification of ReLU Neural Networks with Optimized Abstraction Refinement. NFM 2021: 19-36
• 
  Zhiyong Wu, Ke Meng, Xiukun Yan, Dayin Shi, Benjia Hu:
  Abstraction Refinement Approach for Web Service Selection using Skyline Computations. SERVICES 2021: 66-71
• 
  Guy Katz:
  Invited Talk: Using SMT and Abstraction-Refinement for Neural Network Verification. SMT 2021: 1
• 
  Wael Fatnassi, Yasser Shoukry:
  PolyAR: A Highly Parallelizable Solver For Polynomial Inequality Constraints Using Convex Abstraction Refinement. CoRR abs/2101.04655 (2021)

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