@inproceedings{, author = {Cheng, Chih-Hong and Huang, Chung-Hao and N{\"{u}}hrenberg, Georg}, title = {nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems}, booktitle = {Proceedings of the {IEEE/ACM} International Conference on Computer Aided Design ({ICCAD})}, year = {2019}, month = nov, } @inproceedings{, author = {Cheng, Chih-Hong and N{\"{u}}hrenberg, Georg and Yasuoka, Hirotoshi}, title = {Runtime Monitoring Neuron Activation Patterns}, booktitle = {Design, Automation & Test in Europe Conference & Exhibition}, pages = {300--303}, year = {2019}, month = mar, address = {Florence, Italy}, doi = {10.23919/DATE.2019.8714971}, url = {https://doi.org/10.23919/DATE.2019.8714971}, crossref = {DBLP:conf/date/2019}, } @inproceedings{, author = {Cheng, Chih-Hong and N{\"{u}}hrenberg, Georg and Rue{\ss}, Harald and Yasuoka, Hirotoshi}, title = {Towards Dependability Metrics for Neural Networks}, booktitle = {16th {ACM/IEEE} International Conference on Formal Methods and Models for System Design, {MEMOCODE} 2018, Beijing, China, October 15-18, 2018}, pages = {43--46}, year = {2018}, month = oct, doi = {10.1109/MEMCOD.2018.8556962}, url = {https://doi.org/10.1109/MEMCOD.2018.8556962}, crossref = {DBLP:conf/memocode/2018}, } @inproceedings{, author = {Cheng, Chih-Hong and N{\"{u}}hrenberg, Georg and Huang, Chung-Hao and Rue{\ss}, Harald}, title = {Verification of Binarized Neural Networks via Inter-neuron Factoring - (Short Paper)}, booktitle = {Verified Software. Theories, Tools, and Experiments - 10th International Conference, {VSTTE} 2018, Oxford, UK, July 18-19, 2018, Revised Selected Papers}, pages = {279--290}, year = {2018}, month = jul, doi = {10.1007/978-3-030-03592-1\_16}, url = {https://doi.org/10.1007/978-3-030-03592-1\_16}, crossref = {DBLP:conf/vstte/2018}, } @inproceedings{Cheng2018a, author = {Cheng, Chih-Hong and Diehl, Frederik and Hinz, Gereon Michael and Hamza, Yassine and N{\"{u}}hrenberg, Georg and Rickert, Markus and Rue{\ss}, Harald and Truong Le, Michael}, title = {Neural Networks for Safety-Critical Applications - {C}hallenges, Experiments and Perspectives}, booktitle = {Proceedings of the Design, Automation \& Test in Europe Conference \& Exhibition (DATE)}, pages = {1005--1006}, year = {2018}, month = mar, address = {Dresden, Germany}, abstract = {We propose a methodology for designing dependable Artificial Neural Networks (ANNs) by extending the concepts of understandability, correctness, and validity that are crucial ingredients in existing certification standards. We apply the concept in a concrete case study for designing a highway ANN-based motion predictor to guarantee safety properties such as impossibility for the ego vehicle to suggest moving to the right lane if there exists another vehicle on its right.}, doi = {10.23919/DATE.2018.8342158}, keywords = {autonomous driving, robotics, neural networks, safety}, } @inproceedings{DBLP:journals/corr/ChengNR17, author = {Cheng, Chih-Hong and N{\"{u}}hrenberg, Georg and Rue{\ss}, Harald}, title = {Maximum Resilience of Artificial Neural Networks}, booktitle = {Automated Technology for Verification and Analysis - 15rd International Symposium , {ATVA}}, year = {2017}, }