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Formal verification of neural networks is essential for their deployment in safety-critical areas.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Earlier work this paper cites.
Neural combinatorial optimization with reinforcement learning
Irwan Bello, Hieu Pham, Quoc V Le, Mohammad Norouzi, and Samy Bengio · 2016
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Learning to branch in mixed integer programming
Elias Boutros Khalil, Pierre Le Bodic, Le Song, George Nemhauser, and Bistra Dilkina · 2016
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A machine learning-based approximation of strong branching
Alejandro Marcos Alvarez, Quentin Louveaux, and Louis Wehenkel · 2017
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Learning combinatorial optimization algorithms over graphs
Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, and Le Song · 2017
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Formal verification of piece-wise linear feed-forward neural networks
Ruediger Ehlers · 2017
Earlier work this paper cites.
Reluplex: An efficient smt solver for verifying deep neural networks
Guy Katz, Clark Barrett, David Dill, Kyle Julian, and Mykel Kochenderfer · 2017
Cited alongside, same era.
A unified view of piecewise linear neural network verification
Rudy Bunel, Ilker Turkaslan, Philip H.S Torr, Pushmeet Kohli, and M. Pawan Kumar · 2018
Cited alongside, same era.
Cuts, primal heuristics, and learning to branch for the time-dependent traveling salesman problem
Christoph Hansknecht, Imke Joormann, and Sebastian Stiller · 2018
Cited alongside, same era.
Boosting robustness certification of neural networks
Gagandeep Singh, Timon Gehr, Markus Püschel, and Martin. Vechev · 2018
Cited alongside, same era.
Towards fast computation of certified robustness for relu networks
Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane Boning, Inderjit S Dhillon, and Luca Daniel · 2018
Cited alongside, same era.
Branch and bound for piecewise linear neural network verification
Rudy Bunel, Jingyue Lu, Ilker Turkaslan, Philip H.S Torr, Pushmeet Kohli, and M. Pawan Kumar · 2019
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Exact combinatorial optimization with graph convolutional neural networks
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, and Andrea Lodi · 2019
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The marabou framework for verification and analysis of deep neural networks
Guy Katz, Derek A. Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, and Parth et al. Shah · 2019
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Fast neural network verification via shadow prices
Vicenc Rubies Royo, Roberto Calandra, Dusan M Stipanovic, and Claire Tomlin · 2019
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Evaluating robustness of neural networks with mixed integer programming
Vincent Tjeng, Kai Xiao, and Russ Tedrake · 2019
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Optimization and abstraction: a synergistic approach for analyzing neural network robustness
Greg Anderson, Shankara Pailoor, Isil Dillig, and Swarat. Chaudhuri · 2019
Cited alongside, same era.
Efficient formal safety analysis of neural networks
Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, and Suman Jana
Cited in the paper.
Formal security analysis of neural networks using symbolic intervals
Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, and Suman Jana
Cited in the paper.
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Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong and Zico Kolter · 2019
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