Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study)

2 May 2022

Paolo Tonella

Papers citing "Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study)"

22 / 22 papers shown

Title
MetaSel: A Test Selection Approach for Fine-tuned DNN Models Amin Abbasishahkoo Mahboubeh Dadkhah Lionel C. Briand Dayi Lin 49 0 0 21 Mar 2025
Benchmarking Image Perturbations for Testing Automated Driving Assistance Systems Stefano Carlo Lambertenghi Hannes Leonhard Andrea Stocco AAML 165 2 0 21 Jan 2025
FAN: Fourier Analysis Networks Yihong Dong Ge Li Yongding Tao Xue Jiang Kechi Zhang Jia Li Jing Su Jing Su Jun Zhang Jingjing Xu AI4TS 15 4 0 03 Oct 2024
FAST: Boosting Uncertainty-based Test Prioritization Methods for Neural Networks via Feature Selection Jialuo Chen Jingyi Wang Xiyue Zhang Youcheng Sun Marta Kwiatkowska Jiming Chen Peng Cheng 16 0 0 13 Sep 2024
Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment Shibbir Ahmed Hongyang Gao Hridesh Rajan 21 2 0 26 Jan 2024
Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations Salah Ghamizi Maxime Cordy Yuejun Guo Mike Papadakis And Yves Le Traon 16 1 0 11 Sep 2023
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception Jiyoung Lee Seung Wook Kim Seunghyun Won Joonseok Lee Marzyeh Ghassemi James Thorne Jaeseok Choi O.-Kil Kwon E. Choi 27 1 0 03 Aug 2023
Evaluating the Robustness of Test Selection Methods for Deep Neural Networks Qiang Hu Yuejun Guo Xiaofei Xie Maxime Cordy Wei Ma Mike Papadakis Yves Le Traon NoLa OOD 22 3 0 29 Jul 2023
Neuron Sensitivity Guided Test Case Selection for Deep Learning Testing Dong Huang Qi Bu Yichao Fu Yuhao Qing Junjie Chen Heming Cui AAML 34 2 0 20 Jul 2023
Contrastive inverse regression for dimension reduction Sam Hawke Hengrui Luo Didong Li 16 1 0 20 May 2023
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks Michael Weiss Paolo Tonella AI4CE 15 0 0 05 Apr 2023
DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks Zohreh Aghababaeyan Manel Abdellatif Mahboubeh Dadkhah Lionel C. Briand AAML 31 15 0 08 Mar 2023
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification Roberto Santana Ivan Hidalgo-Cenalmor Unai Garciarena A. Mendiburu Jose A. Lozano 27 2 0 05 Mar 2023
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering Yongxin Guo Xiaoying Tang Tao R. Lin OOD FedML 30 8 0 29 Jan 2023
To Softmax, or not to Softmax: that is the question when applying Active Learning for Transformer Models Julius Gonsior C. Falkenberg Silvio Magino Anja Reusch Maik Thiele Wolfgang Lehner UQCV 36 7 0 06 Oct 2022
CheapET-3: Cost-Efficient Use of Remote DNN Models Michael Weiss 36 1 0 24 Aug 2022
Generating and Detecting True Ambiguity: A Forgotten Danger in DNN Supervision Testing Michael Weiss A. Gómez Paolo Tonella AAML 18 6 0 21 Jul 2022
Guiding the retraining of convolutional neural networks against adversarial inputs Francisco Durán Silverio Martínez-Fernández Michael Felderer Xavier Franch AAML 30 1 0 08 Jul 2022
Hierarchical Distribution-Aware Testing of Deep Learning Wei Huang Xingyu Zhao Alec Banks V. Cox Xiaowei Huang OOD AAML 34 10 0 17 May 2022
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems Andrea Stocco Brian Pulfer Paolo Tonella 27 67 0 21 Dec 2021
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring Michael Weiss Paolo Tonella AAML 45 29 0 01 Feb 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015