Deep Neural Network Compression for Aircraft Collision Avoidance Systems

9 October 2018

Mykel J. Kochenderfer

Michael P. Owen

Papers citing "Deep Neural Network Compression for Aircraft Collision Avoidance Systems"

32 / 32 papers shown

Title
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks Matthias König Xiyue Zhang Holger H. Hoos Marta Kwiatkowska Jan N. van Rijn AAML 45 1 0 14 Jun 2024
System Safety Monitoring of Learned Components Using Temporal Metric Forecasting Sepehr Sharifi Andrea Stocco Lionel C. Briand AI4TS 48 1 0 21 May 2024
Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions László Antal Hana Masara Erika Ábrahám 36 0 0 16 Nov 2023
Safety, Trust, and Ethics Considerations for Human-AI Teaming in Aerospace Control Kerianne L. Hobbs Bernard Li 27 2 0 15 Nov 2023
Incremental Randomized Smoothing Certification Shubham Ugare Tarun Suresh Debangshu Banerjee Gagandeep Singh Sasa Misailovic AAML 38 8 0 31 May 2023
Vertex-based reachability analysis for verifying ReLU deep neural networks João G. Zago E. Camponogara Eric A. Antonelo AAML 29 2 0 27 Jan 2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks David Boetius Stefan Leue Tobias Sutter 33 4 0 26 Jan 2023
QEBVerif: Quantization Error Bound Verification of Neural Networks Yedi Zhang Fu Song Jun Sun MQ 26 11 0 06 Dec 2022
Reward Function Optimization of a Deep Reinforcement Learning Collision Avoidance System Cooper Cone Michael Owen Luis E. Alvarez Marc Brittain 24 2 0 01 Dec 2022
A Hybrid Partitioning Strategy for Backward Reachability of Neural Feedback Loops Nicholas Rober Michael Everett Songan Zhang Jonathan P. How 37 9 0 14 Oct 2022
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems Nicholas Rober Sydney M. Katz Chelsea Sidrane Esen Yel Michael Everett Mykel J. Kochenderfer Jonathan P. How 35 26 0 28 Sep 2022
Toward Certification of Machine-Learning Systems for Low Criticality Airborne Applications Konstantin Dmitriev J. Schumann F. Holzapfel 33 20 0 28 Sep 2022
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks Jiaxiang Liu Yunhan Xing Xiaomu Shi Fu Song Zhiwu Xu Zhong Ming 24 10 0 02 Jul 2022
Neural Network Verification with Proof Production Omri Isac Clark W. Barrett Hao Fei Guy Katz AAML 35 20 0 01 Jun 2022
Long Short-Term Memory for Spatial Encoding in Multi-Agent Path Planning Marc R. Schlichting S. Notter W. Fichter 26 2 0 21 Mar 2022
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators Lois Orosa Skanda Koppula Yaman Umuroglu Konstantinos Kanellopoulos Juan Gómez Luna Michaela Blott K. Vissers O. Mutlu 46 4 0 04 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
Croesus: Multi-Stage Processing and Transactions for Video-Analytics in Edge-Cloud Systems Samaa Gazzaz Vishal Chakraborty Faisal Nawab 41 10 0 31 Dec 2021
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees Feisi Fu Wenchao Li KELM AAML 41 26 0 14 Oct 2021
Verifying Low-dimensional Input Neural Networks via Input Quantization Kai Jia Martin Rinard AAML 30 14 0 18 Aug 2021
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs Christopher A. Strong Sydney M. Katz Anthony Corso Mykel J. Kochenderfer 37 2 0 09 Jun 2021
Transfer Learning for Efficient Iterative Safety Validation Anthony Corso Mykel J. Kochenderfer 19 5 0 09 Dec 2020
Abstract Neural Networks Matthew Sotoudeh Aditya V. Thakur 8 19 0 11 Sep 2020
Abstraction based Output Range Analysis for Neural Networks P. Prabhakar Zahra Rahimi Afzal 33 62 0 18 Jul 2020
DeepAbstract: Neural Network Abstraction for Accelerating Verification P. Ashok Vahid Hashemi Jan Křetínský S. Mohr 19 49 0 24 Jun 2020
Robustness Certification of Generative Models M. Mirman Timon Gehr Martin Vechev AAML 43 22 0 30 Apr 2020
Parallelization Techniques for Verifying Neural Networks Haoze Wu Alex Ozdemir Aleksandar Zeljić A. Irfan Kyle D. Julian D. Gopinath Sadjad Fouladi Guy Katz C. Păsăreanu Clark W. Barrett 27 59 0 17 Apr 2020
dtControl: Decision Tree Learning Algorithms for Controller Representation P. Ashok Mathias Jackermeier Pushpak Jagtap Jan Křetínský Maximilian Weininger Majid Zamani 16 30 0 12 Feb 2020
ReluDiff: Differential Verification of Deep Neural Networks Brandon Paulsen Jingbo Wang Chao Wang 27 53 0 10 Jan 2020
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 36 392 0 15 Mar 2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification Jianlin Li Pengfei Yang Jiangchao Liu Liqian Chen Xiaowei Huang Lijun Zhang AAML 24 80 0 26 Feb 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,842 0 03 Feb 2017