| Hybrid. ai: A learning search engine for large-scale structured data S Soderman, A Kola, M Podkorytov, M Geyer, M Gubanov Companion Proceedings of the The Web Conference 2018, 1507-1514, 2018 | 13 | 2018 |
| SAD: Saliency-based defenses against adversarial examples R Tran, D Patrick, M Geyer, A Fernandez arXiv preprint arXiv:2003.04820, 2020 | 3 | 2020 |
| An exact kernel equivalence for finite classification models BW Bell, M Geyer, D Glickenstein, AS Fernandez, J Moore Topological, Algebraic and Geometric Learning Workshops 2023, 206-217, 2023 | 1 | 2023 |
| Building performance evaluation framework of foundation models for nonproliferation applications A Skurikhin, G Flynn, M Geyer, G Gopalan, N Klein, J Moore, M Myshatyn, ... Proceedings of the 2nd Joint Annual Meeting of the Institute of Nuclear …, 2023 | 1 | 2023 |
| Reconstructive training for real-world robustness in image classification D Patrick, M Geyer, R Tran, A Fernandez Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 1 | 2022 |
| Persistent Classification: A New Approach to Stability of Data and Adversarial Examples B Bell, M Geyer, D Glickenstein, K Hamm, C Scheidegger, A Fernandez, ... arXiv preprint arXiv:2404.08069, 2024 | | 2024 |
| Exact Path Kernels Naturally Decompose Model Predictions M Geyer, BW Bell, D Glickenstein, AS Fernandez, J Moore | | 2023 |
| On the Relationship Between Data Manifolds and Adversarial Examples M Geyer, BW Bell, AS Fernandez, J Moore | | 2023 |
| Analyzing the Geometric Structure of Deep Learning Decision Boundaries M Geyer The University of Texas at San Antonio, 2023 | | 2023 |
Amanda S. FernandezAssistant Professor, University of Texas at San AntonioVerified email at utsa.edu
