Kyle Julian

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 13

Top Topics

Planning Under Uncertainty

Multilayer Perceptron

Top Venues

Publications

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. CAV (2) (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 (2024)
Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer
Reluplex: a calculus for reasoning about deep neural networks. Formal Methods Syst. Des. 60 (1) (2022)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. FMCAD (2020)
Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Ahmed Irfan, Kyle Julian, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett
Parallelization Techniques for Verifying Neural Networks. CoRR (2020)
Guy Katz, Derek A. Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljic, David L. Dill, Mykel J. Kochenderfer, Clark W. Barrett
The Marabou Framework for Verification and Analysis of Deep Neural Networks. CAV (1) (2019)
Maxime Bouton, Kyle Julian, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer
Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty. AAMAS (2018)
Lindsey Kuper, Guy Katz, Justin Gottschlich, Kyle Julian, Clark W. Barrett, Mykel J. Kochenderfer
Toward Scalable Verification for Safety-Critical Deep Networks. CoRR (2018)
Maxime Bouton, Kyle Julian, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer
Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty. CoRR (2018)
John Mern, Kyle Julian, Rachael E. Tompa, Mykel J. Kochenderfer
Visual Depth Mapping from Monocular Images using Recurrent Convolutional Neural Networks. CoRR (2018)
Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer
Towards Proving the Adversarial Robustness of Deep Neural Networks. FVAV@iFM (2017)
Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. CoRR (2017)
Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. CAV (1) (2017)