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Alexander Bronstein

Nikolaus Dräger

Tristan Gollmart

Sai Maddipatla

Marco Pegoraro

Nabin Sahoo

Dmitry Solovey

Baoying Wang

Shuqin Zhang



9 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 | Epub ahead of print | Journal Article | IST-REx-ID: 22268 | OA | PlanS
S. A. Maddipatla et al., “Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles,” Nature Biotechnology. Springer Nature, 2026.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | PubMed | Europe PMC
 
2026 | Published | Conference Paper | IST-REx-ID: 22722 | OA
M. I. Bojan et al., “Representing local protein environments with machine learning force fields,” in 14th International Conference on Learning Representations, Rio de Janeiro, Brazil, 2026, vol. 2026, pp. 100760–100799.
[Published Version] View | Files available | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 21246 | OA | PlanS
I. Kamai, A. M. Bronstein, and H. B. Perets, “Machine Learning inference of stellar properties using integrated photometric and spectroscopic data,” The Astrophysical Journal, vol. 994. IOP Publishing, 2025.
[Published Version] View | Files available | DOI | arXiv
 
2025 | Published | Conference Paper | IST-REx-ID: 21327 | OA
S. A. Maddipatla et al., “Inverse problems with experiment-guided AlphaFold,” in Proceedings of the 42nd International Conference on Machine Learning, Vancouver, Canada, 2025, vol. 267, pp. 42366–42393.
[Published Version] View | Files available | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 20100 | OA | PlanS
S. Vedula, A. M. Bronstein, and A. Marx, “Improving prediction accuracy in chimeric proteins with windowed multiple sequence alignment,” Computational and Structural Biotechnology Journal, vol. 27. Elsevier, pp. 3292–3298, 2025.
[Published Version] View | Files available | DOI | WoS
 
2025 | Research Data Reference | IST-REx-ID: 20103 | OA
S. Vedula, A. M. Bronstein, and A. Marx, “Replication Data for: ‘Improving Prediction Accuracy in Chimeric Proteins with Windowed Multiple Sequence Alignment.’” Harvard Dataverse, 2025.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2025 | Published | Conference Paper | IST-REx-ID: 20707 | OA
B. Gahtan, S. Vedula, G. Samuelly Leichtag, E. Kodesh, and A. M. Bronstein, “From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling,” in Proceedings of the 27th International Conference on Multimodal Interaction, Canberra, Australia, 2025, pp. 60–77.
[Published Version] View | Files available | DOI | arXiv
 
2025 | Published | Journal Article | IST-REx-ID: 19595 | OA
Y. Davidson, A. Philipp, S. Chakraborty, A. M. Bronstein, and R. Gershoni-Poranne, “How local is ‘local’? Deep learning reveals locality of the induced magnetic field of polycyclic aromatic hydrocarbons,” Journal of Chemical Physics, vol. 162, no. 14. AIP Publishing, 2025.
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 

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