Evaluation of multi feature fusion at score-level for appearance-based person re-identification. - Markus Eisenbach 001; Alexander Kolarow; Alexander Vorndran; Julia Niebling; Horst-Michael Gross (IJCNN, 2015)

Eigenvalue conditions for induced subgraphs. - Jochen Harant; Julia Niebling; Sebastian Richter (Discuss. Math. Graph Theory, 2015)

A Branch-and-Bound-Based Algorithm for Nonconvex Multiobjective Optimization. - Julia Niebling; Gabriele Eichfelder (SIAM J. Optim., 2019)

Analysis of Railway Track Irregularities with Convolutional Autoencoders and Clustering Algorithms. - Julia Niebling; Benjamin Baasch; Anna M. Kruspe (EDCC Workshops, 2020)

An algorithmic approach to multiobjective optimization with decision uncertainty. - Gabriele Eichfelder; Julia Niebling; Stefan Rocktäschel (J. Glob. Optim., 2020)

Solving Multiobjective Mixed Integer Convex Optimization Problems. - Marianna De Santis; Gabriele Eichfelder; Julia Niebling; Stefan Rocktäschel (SIAM J. Optim., 2020)

Nonconvex constrained optimization by a filtering branch and bound. - Gabriele Eichfelder; Kathrin Klamroth; Julia Niebling (J. Glob. Optim., 2021)

Robust Distribution-Shift Aware Sar-Optical data Fusion for Multi-Label Scene Classification. - Jakob Gawlikowski; Sudipan Saha; Julia Niebling; Xiao Xiang Zhu 001 (IGARSS, 2022)

Analysing the Interactions Between Training Dataset Size, Label Noise and Model Performance in Remote Sensing Data. - Jonas Gütter; Julia Niebling; Xiao Xiang Zhu 001 (IGARSS, 2022)

Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks. - Frank Nussbaum; Jakob Gawlikowski; Julia Niebling (NeurIPS, 2022)

Is it worth it? An experimental comparison of six deep- and classical machine learning methods for unsupervised anomaly detection in time series. - Ferdinand Rewicki; Joachim Denzler; Julia Niebling (CoRR, 2022)

Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation. - Katharina Fogelberg; Sireesha Chamarthi; Roman C. Maron; Julia Niebling; Titus J. Brinker (CoRR, 2023)

Mitigating the Influence of Domain Shift in Skin Lesion Classification: A Benchmark Study of Unsupervised Domain Adaptation Methods on Dermoscopic Images. - Sireesha Chamarthi; Katharina Fogelberg; Roman C. Maron; Titus J. Brinker; Julia Niebling (CoRR, 2023)

Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification. - Jakob Gawlikowski; Sudipan Saha; Julia Niebling; Xiao Xiang Zhu 001 (EURASIP J. Adv. Signal Process., 2023)

Exploiting Text-Image Latent Spaces for the Description of Visual Concepts. - Laines Schmalwasser; Jakob Gawlikowski; Joachim Denzler; Julia Niebling (ICPR (33), 2024)

Functional Tensor Decompositions for Physics-Informed Neural Networks. - Sai Karthikeya Vemuri; Tim Büchner; Julia Niebling; Joachim Denzler (ICPR (25), 2024)

Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-Regenerative Life Support System Telemetry. - Ferdinand Rewicki; Jakob Gawlikowski; Julia Niebling; Joachim Denzler (ECML/PKDD (9), 2024)

Anomalous Agreement: How to find the Ideal Number of Anomaly Classes in Correlated, Multivariate Time Series Data. - Ferdinand Rewicki; Joachim Denzler; Julia Niebling (CoRR, 2025)

FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks. - Laines Schmalwasser; Niklas Penzel; Joachim Denzler; Julia Niebling (CoRR, 2025)

Analyzing and Fine-Tuning Whisper Models for Multilingual Pilot Speech Transcription in the Cockpit. - Kartheek Kumar Reddy Nareddy; Sarah Ternus; Julia Niebling (CoRR, 2025)