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PaRoT: A Practical Framework for Robust Deep Neural Network Training
v1v2v3 (latest)

PaRoT: A Practical Framework for Robust Deep Neural Network Training

NASA Formal Methods (NFM), 2020
7 January 2020
Edward W. Ayers
Francisco Eiras
Majd Hawasly
I. Whiteside
    OOD
ArXiv (abs)PDFHTML

Papers citing "PaRoT: A Practical Framework for Robust Deep Neural Network Training"

9 / 9 papers shown
Title
Efficient Error Certification for Physics-Informed Neural Networks
Efficient Error Certification for Physics-Informed Neural NetworksInternational Conference on Machine Learning (ICML), 2023
Francisco Eiras
Adel Bibi
Rudy Bunel
Krishnamurthy Dvijotham
Juil Sock
M. P. Kumar
PINN
219
3
0
17 May 2023
Certifying Ensembles: A General Certification Theory with
  S-Lipschitzness
Certifying Ensembles: A General Certification Theory with S-LipschitznessInternational Conference on Machine Learning (ICML), 2023
Aleksandar Petrov
Francisco Eiras
Amartya Sanyal
Juil Sock
Adel Bibi
UQCV
162
1
0
25 Apr 2023
Perspectives on the System-level Design of a Safe Autonomous Driving
  Stack
Perspectives on the System-level Design of a Safe Autonomous Driving StackAI Communications (AC), 2022
Majd Hawasly
Jonathan Sadeghi
Morris Antonello
Stefano V. Albrecht
John Redford
S. Ramamoorthy
92
5
0
29 Jul 2022
CheckINN: Wide Range Neural Network Verification in Imandra (Extended)
CheckINN: Wide Range Neural Network Verification in Imandra (Extended)ACM-SIGPLAN International Conference on Principles and Practice of Declarative Programming (PPDP), 2022
Remi Desmartin
Grant Passmore
Ekaterina Komendantskaya
M. Daggitt
132
5
0
21 Jul 2022
Verifiable Goal Recognition for Autonomous Driving with Occlusions
Verifiable Goal Recognition for Autonomous Driving with OcclusionsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022
Cillian Brewitt
Massimiliano Tamborski
Cheng Wang
Stefano V. Albrecht
135
14
0
28 Jun 2022
The Role of Explainability in Assuring Safety of Machine Learning in
  Healthcare
The Role of Explainability in Assuring Safety of Machine Learning in HealthcareIEEE Transactions on Emerging Topics in Computing (TETC), 2021
Yan Jia
John McDermid
T. Lawton
Ibrahim Habli
193
61
0
01 Sep 2021
How to Certify Machine Learning Based Safety-critical Systems? A
  Systematic Literature Review
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature ReviewInternational Conference on Automated Software Engineering (ASE), 2021
Florian Tambon
Gabriel Laberge
Le An
Amin Nikanjam
Paulina Stevia Nouwou Mindom
Y. Pequignot
Foutse Khomh
G. Antoniol
E. Merlo
François Laviolette
368
79
0
26 Jul 2021
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned
  Decision Trees for Autonomous Driving
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous DrivingIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021
Cillian Brewitt
Bálint Gyevnár
Samuel Garcin
Stefano V. Albrecht
216
31
0
10 Mar 2021
PILOT: Efficient Planning by Imitation Learning and Optimisation for
  Safe Autonomous Driving
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous DrivingIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2020
H. Pulver
Francisco Eiras
L. Carozza
Majd Hawasly
Stefano V. Albrecht
S. Ramamoorthy
196
23
0
01 Nov 2020
1