Overview
Education/Academic qualification
Math-Applied, Doctorate Degree
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Dive into the research topics where Nina Gottschling is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Lightning UQ Box: Uncertainty Quantification for Neural Networks
Lehmann, N., Gottschling, N. M., Gawlikowski, J., Stewart, A. J., Depeweg, S. & Nalisnick, E., 2025, In: Journal of Machine Learning Research. 26Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
The Troublesome Kernel: On Hallucinations, No Free Lunches, and the Accuracy-Stability Tradeoff in Inverse Problems
Gottschling, N. M., Antun, V., Hansen, A. C. & Adcock, B., 2025, In: SIAM-ASA Journal on Uncertainty Quantification. 67, 1, p. 73-104 32 p.Research output: Contribution to journal › Article › peer-review
19 Scopus citations -
Efficient Data Source Relevance Quantification for Multi-Source Neural Networks
Gawlikowski, J. & Gottschling, N. M., 2024.Research output: Contribution to conference › Paper › peer-review
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Uncertainty-Aware Learning With Label Noise for Glacier Mass Balance Modeling
Diaconu, C. A. & Gottschling, N. M., 2024, In: IEEE Geoscience and Remote Sensing Letters. 21, p. 1-5 5 p., 2000505.Research output: Contribution to journal › Article › peer-review
Open Access3 Scopus citations -
Uncertainty-aware Unsupervised Machine Learning to Draw Coastline
Karmakar, C., Gottschling, N. M., Camero, A. & Datcu, M., 2024, 2024 IEEE Conference on Advanced Topics on Measurement and Simulation, ATOMS 2024. Institute of Electrical and Electronics Engineers Inc., p. 27-30 4 p. (2024 IEEE Conference on Advanced Topics on Measurement and Simulation, ATOMS 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Scopus citations