Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

3 February 2017

Mykel Kochenderfer

Papers citing "Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks"

50 / 346 papers shown

Title
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming Robin Brown Edward Schmerling Navid Azizan Marco Pavone AAML 24 14 0 06 Mar 2022
A Quantitative Geometric Approach to Neural-Network Smoothness Zehao Wang Gautam Prakriya S. Jha 37 13 0 02 Mar 2022
Neuro-Symbolic Verification of Deep Neural Networks Xuan Xie Kristian Kersting Daniel Neider AAML NAI 27 15 0 02 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis Thomas Fel Mélanie Ducoffe David Vigouroux Rémi Cadène Mikael Capelle C. Nicodeme Thomas Serre AAML 26 41 0 15 Feb 2022
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers M. Daggitt Wen Kokke R. Atkey Luca Arnaboldi Ekaterina Komendantskaya 23 5 0 10 Feb 2022
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers B. Liao Chih-Hong Cheng Hasan Esen Alois Knoll AAML 26 1 0 08 Feb 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 21 16 0 04 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Aleksandrovich Pautov Olesya Kuznetsova Nurislam Tursynbek Aleksandr Petiushko Ivan V. Oseledets 39 5 0 02 Feb 2022
Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State Backreachability Stanley Bak Hoang-Dung Tran AAML 32 15 0 17 Jan 2022
Systems Challenges for Trustworthy Embodied Systems Harald Ruess 13 2 0 10 Jan 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks Matan Ostrovsky Clark W. Barrett Guy Katz 40 26 0 06 Jan 2022
On the Minimal Adversarial Perturbation for Deep Neural Networks with Provable Estimation Error Fabio Brau Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 24 7 0 04 Jan 2022
Toward the Analysis of Graph Neural Networks Thanh-Dat Nguyen Thanh Le-Cong Thanh-Hung Nguyen X. Le Quyet-Thang Huynh GNN 19 3 0 01 Jan 2022
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification A. Ćiprijanović Diana Kafkes Gregory F. Snyder F. Sánchez G. Perdue K. Pedro Brian D. Nord Sandeep Madireddy Stefan M. Wild AAML 42 15 0 28 Dec 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 32 6 0 09 Dec 2021
SaDe: Learning Models that Provably Satisfy Domain Constraints Kshitij Goyal Sebastijan Dumancic Hendrik Blockeel ALM 25 5 0 01 Dec 2021
Adaptive Image Transformations for Transfer-based Adversarial Attack Zheng Yuan Jie Zhang Shiguang Shan OOD 21 25 0 27 Nov 2021
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking Xidan Song Edoardo Manino Luiz Sena E. Alves Eddie Batista de Lima Filho I. Bessa M. Luján Lucas C. Cordeiro 37 5 0 25 Nov 2021
Fast BATLLNN: Fast Box Analysis of Two-Level Lattice Neural Networks James Ferlez Haitham Khedr Yasser Shoukry 24 11 0 17 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 26 14 0 02 Nov 2021
MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks Nicholas Hoernle Rafael-Michael Karampatsis Vaishak Belle Y. Gal 24 59 0 02 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 29 76 0 02 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 27 18 0 29 Oct 2021
QuantifyML: How Good is my Machine Learning Model? Mario Gleirscher D. Gopinath C. Păsăreanu 20 2 0 25 Oct 2021
RoMA: a Method for Neural Network Robustness Measurement and Assessment Natan Levy Guy Katz OOD AAML 10 13 0 21 Oct 2021
Minimal Multi-Layer Modifications of Deep Neural Networks Idan Refaeli Guy Katz KELM AAML 35 15 0 18 Oct 2021
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees Feisi Fu Wenchao Li KELM AAML 41 26 0 14 Oct 2021
Assessment of Neural Networks for Stream-Water-Temperature Prediction S. Mohr Konstantina Drainas J. Geist 23 3 0 08 Oct 2021
Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems Lisa Oakley Alina Oprea S. Tripakis AAML 13 0 0 05 Oct 2021
Neural Network Verification in Control M. Everett AAML 34 16 0 30 Sep 2021
Lyapunov-stable neural-network control Hongkai Dai Benoit Landry Lujie Yang Marco Pavone Russ Tedrake 17 119 0 29 Sep 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Aleksandrovich Pautov Nurislam Tursynbek Marina Munkhoeva Nikita Muravev Aleksandr Petiushko Ivan V. Oseledets AAML 52 15 0 22 Sep 2021
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation Chuangchuang Sun Dong-Ki Kim Jonathan P. How AAML 31 19 0 14 Sep 2021
Learning Density Distribution of Reachable States for Autonomous Systems Yue Meng Dawei Sun Zeng Qiu Md Tawhid Bin Waez Chuchu Fan 77 19 0 14 Sep 2021
Mini Cheetah, the Falling Cat: A Case Study in Machine Learning and Trajectory Optimization for Robot Acrobatics Vince Kurtz He Li Patrick M. Wensing Hai Lin 54 29 0 09 Sep 2021
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results Stanley Bak Changliu Liu Taylor T. Johnson NAI 22 112 0 31 Aug 2021
Reachability Is NP-Complete Even for the Simplest Neural Networks Marco Salzer M. Lange 22 26 0 30 Aug 2021
Scalable and Modular Robustness Analysis of Deep Neural Networks Yuyi Zhong Quang-Trung Ta Tianzuo Luo Fanlong Zhang Siau-Cheng Khoo 23 3 0 26 Aug 2021
Verifying Low-dimensional Input Neural Networks via Input Quantization Kai Jia Martin Rinard AAML 30 13 0 18 Aug 2021
Reachability Analysis of Neural Feedback Loops M. Everett Golnaz Habibi Chuangchuang Sun Jonathan P. How 19 53 0 09 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Neural Network Branch-and-Bound for Neural Network Verification Florian Jaeckle Jingyue Lu M. P. Kumar 18 8 0 27 Jul 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 30 66 0 26 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 26 17 0 18 Jul 2021
Probabilistic Verification of Neural Networks Against Group Fairness Bing-Jie Sun Jun Sun Ting Dai Lijun Zhang AAML 21 22 0 18 Jul 2021
POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems Chao Huang Jiameng Fan Zhilu Wang Yixuan Wang Weichao Zhou Jiajun Li Xin Chen Wenchao Li Qi Zhu 32 48 0 25 Jun 2021
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe Panagiotis Vlantis Leila J. Bridgeman Michael M. Zavlanos 40 0 0 22 Jun 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021