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2020 – today
- 2024
[i4]Stephen Casper, Jieun Yun, Joonhyuk Baek, Yeseong Jung, Minhwan Kim, Kiwan Kwon, Saerom Park, Hayden Moore, David Shriver, Marissa Connor, Keltin Grimes, Angus Nicolson, Arush Tagade, Jessica Rumbelow, Hieu Minh Nguyen, Dylan Hadfield-Menell:
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability. CoRR abs/2404.02949 (2024)- [i3]Keltin Grimes, Marco Christiani, David Shriver, Marissa Connor:
Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing. CoRR abs/2412.13341 (2024) - 2023
- [j1]Meriel von Stein
, David Shriver, Sebastian G. Elbaum:
DeepManeuver: Adversarial Test Generation for Trajectory Manipulation of Autonomous Vehicles. IEEE Trans. Software Eng. 49(10): 4496-4509 (2023) - [c9]Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Deeper Notions of Correctness in Image-Based DNNs: Lifting Properties from Pixel to Entities. ESEC/SIGSOFT FSE 2023: 2122-2126 - 2021
- [c8]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
DNNV: A Framework for Deep Neural Network Verification. CAV (1) 2021: 137-150 - [c7]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Artifact: Reducing DNN Properties to Enable Falsification with Adversarial Attacks. ICSE (Companion Volume) 2021: 162-163 - [c6]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Reducing DNN Properties to Enable Falsification with Adversarial Attacks. ICSE 2021: 275-287 - [c5]Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Distribution Models for Falsification and Verification of DNNs. ASE 2021: 317-329 - [d6]David Shriver, Sebastian G. Elbaum, Matthew Dwyer:
Reducing DNN Properties to Enable Falsification with Adversarial Attacks. Zenodo, 2021
- [d5]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Artifact for DNNV: A Framework for Deep Neural Network Verification. Version 1. Zenodo, 2021 [all versions] - [d4]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Artifact for DNNV: A Framework for Deep Neural Network Verification. Version 2. Zenodo, 2021 [all versions] - [d3]Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew Dwyer:
Distribution Models for Falsification and Verification of DNNs. Version 1. Zenodo, 2021 [all versions] - [d2]Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Distribution Models for Falsification and Verification of DNNs. Version 1. Zenodo, 2021 [all versions] - [d1]Felipe Toledo, David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
Distribution Models for Falsification and Verification of DNNs. Version 2. Zenodo, 2021 [all versions] - [i2]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer:
DNNV: A Framework for Deep Neural Network Verification. CoRR abs/2105.12841 (2021) - 2020
- [c4]Dong Xu, David Shriver, Matthew B. Dwyer, Sebastian G. Elbaum:
Systematic Generation of Diverse Benchmarks for DNN Verification. CAV (1) 2020: 97-121
2010 – 2019
- 2019
- [c3]David Shriver, Sebastian G. Elbaum, Matthew B. Dwyer, David S. Rosenblum:
Evaluating Recommender System Stability with Influence-Guided Fuzzing. AAAI 2019: 4934-4942 - [i1]David Shriver, Dong Xu, Sebastian G. Elbaum, Matthew B. Dwyer:
Refactoring Neural Networks for Verification. CoRR abs/1908.08026 (2019) - 2018
- [c2]David Shriver:
Toward the development of richer properties for recommender systems. ICSE (Companion Volume) 2018: 173-174 - 2017
- [c1]David Shriver, Sebastian G. Elbaum, Kathryn T. Stolee:
At the End of Synthesis: Narrowing Program Candidates. ICSE-NIER 2017: 19-22
Coauthor Index
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