225 results on '"Guy Katz"'
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52. Towards Repairing Scenario-Based Models with Rich Events.
53. An SMT-Based Approach for Verifying Binarized Neural Networks.
54. Verifying learning-augmented systems.
55. Towards Scalable Verification of Deep Reinforcement Learning.
56. Pruning and Slicing Neural Networks using Formal Verification.
57. Simplifying Neural Networks Using Formal Verification.
58. Guarded Deep Learning using Scenario-based Modeling.
59. Augmenting Deep Neural Networks with Scenario-Based Guard Rules.
60. An Abstraction-Based Framework for Neural Network Verification.
61. Minimal Modifications of Deep Neural Networks using Verification.
62. Verifying Recurrent Neural Networks Using Invariant Inference.
63. Parallelization Techniques for Verifying Neural Networks.
64. veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System.
65. BBReach: Tight and Scalable Black-Box Reachability Analysis of Deep Reinforcement Learning Systems.
66. Verifying Learning-Based Robotic Navigation Systems.
67. Tighter Abstract Queries in Neural Network Verification.
68. Towards Formal Approximated Minimal Explanations of Neural Networks.
69. Constrained Reinforcement Learning for Robotics via Scenario-Based Programming.
70. Efficiently Finding Adversarial Examples with DNN Preprocessing.
71. Enhancing Deep Reinforcement Learning with Scenario-Based Modeling.
72. On-the-Fly Construction of Composite Events in Scenario-Based Modeling using Constraint Solvers.
73. Executing Scenario-Based Specification with Dynamic Generation of Rich Events.
74. The Marabou Framework for Verification and Analysis of Deep Neural Networks.
75. Verifying Deep-RL-Driven Systems.
76. DeepSafe: A Data-Driven Approach for Assessing Robustness of Neural Networks.
77. Towards Scalable Verification of RL-Driven Systems.
78. Minimal Multi-Layer Modifications of Deep Neural Networks.
79. RoMA: a Method for Neural Network Robustness Measurement and Assessment.
80. Efficient Distributed Execution of Multi-component Scenario-Based Models.
81. Distributing Scenario-based Models: A Replicate-and-Project Approach.
82. Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks.
83. SMTCoq: A Plug-In for Integrating SMT Solvers into Coq.
84. Invited Talk: Using SMT and Abstraction-Refinement for Neural Network Verification.
85. Wise Computing: Toward Endowing System Development with Proactive Wisdom.
86. An SMT-Based Approach for Verifying Binarized Neural Networks.
87. Global Optimization of Objective Functions Represented by ReLU Networks.
88. An Initial Wise Development Environment for Behavioral Models.
89. Six (Im)possible Things before Breakfast: Building-Blocks and Design-Principles for Wise Computing.
90. Scenario-Based Modeling and Synthesis for Reactive Systems with Dynamic System Structure in ScenarioTools.
91. Lazy proofs for DPLL(T)-based SMT solvers.
92. ScenarioTools - A tool suite for the scenario-based modeling and analysis of reactive systems.
93. The Effect of Concurrent Programming Idioms on Verification - A Position Paper.
94. On the Succinctness of Idioms for Concurrent Programming.
95. Theory-Aided Model Checking of Concurrent Transition Systems.
96. Simplifying Neural Networks with the Marabou Verification Engine.
97. An Abstraction-Based Framework for Neural Network Verification.
98. DNN Verification, Reachability, and the Exponential Function Problem
99. RheumMadness: Creating an Online Community of Inquiry in Rheumatology
100. First Steps Towards a Wise Development Environment for Behavioral Models.
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