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11 Publications


2026 | Accepted | Conference Paper | IST-REx-ID: 21949 | OA
T. Shor, M. Freiman, C. Baskin, and A. M. Bronstein, “T1-PILOT: Physics-informed learned optimized trajectories for T1 mapping acceleration,” in Medical Imaging with Deep Learning, Taipei, Taiwan, vol. 315, pp. 1969–1982.
[Published Version] View | Files available | Download Published Version (ext.)
 

2026 | Published | Conference Paper | IST-REx-ID: 22146 | OA
N. Kalinin and J. D. Andersson, “Learning rate scheduling with matrix factorization for private training,” in 7th Symposium on Foundations of Responsible Computing, Cambridge, MA; United States, 2026, vol. 368.
[Published Version] View | Files available | DOI | arXiv
 

2026 | Published | Conference Paper | IST-REx-ID: 22294 | OA
A. Hatua, T. Nguyen, F. Cano Cordoba, and A. Sung, “Machine unlearning using forgetting neural networks,” in Proceedings of the 18th International Conference on Agents and Artificial Intelligence, Marbella, Spain, 2026, vol. 2, pp. 1536–1546.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2025 | Published | Thesis | PhD | IST-REx-ID: 19456 | OA
A. D. Cumpelik, “The role of prefrontal spatial coding in supporting a contextual association task,” Institute of Science and Technology Austria, 2025.
[Published Version] View | Files available | DOI
 

2023 | Published | Conference Paper | IST-REx-ID: 12976 | OA
K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition policies for fused multi-material 3D printing,” in 2023 IEEE International Conference on Robotics and Automation, London, United Kingdom, 2023, vol. 2023, pp. 12345–12352.
[Submitted Version] View | Files available | DOI | WoS
 

2022 | Published | Thesis | PhD | IST-REx-ID: 10799 | OA
N. H. Konstantinov, “Robustness and fairness in machine learning,” Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 

2022 | Published | Journal Article | IST-REx-ID: 10802 | OA
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
[Published Version] View | Files available | arXiv
 

2022 | Published | Thesis | PhD | IST-REx-ID: 11362 | OA
M. Lechner, “Learning verifiable representations,” Institute of Science and Technology Austria, 2022.
[Published Version] View | Files available | DOI
 

2021 | Published | Book Chapter | IST-REx-ID: 9756
W. Kaufmann, D. Kleindienst, H. Harada, and R. Shigemoto, “High-Resolution localization and quantitation of membrane proteins by SDS-digested freeze-fracture replica labeling (SDS-FRL),” in Receptor and Ion Channel Detection in the Brain, vol. 169, New York: Humana Press, 2021, pp. 267–283.
View | Files available | DOI
 

2019 | Submitted | Preprint | IST-REx-ID: 11627 | OA
S. N. Breton et al., “Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2019 | Submitted | Preprint | IST-REx-ID: 11630 | OA
A. L. Saux, L. A. Bugnet, S. Mathur, S. N. Breton, and R. A. Garcia, “Automatic classification of K2 pulsating stars using machine learning techniques,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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