Article (botache2024enhancing)
Botache, D.; Decke, J.; Ripken, W.; Dornipati, A.; Götz-Hahn, F.; Ayeb, M. & Sick, B.
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
arXiv e-prints,
2024, arXiv:2309.13179v2
Inproceedings (decke2024efficient)
Decke, J.; Jenß, A.; Sick, B. & Gruhl, C.
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing
Springer,
2024
Inproceedings (decke2024structured)
Decke, J.; Wünsch, O.; Sick, B. & Gruhl, C.
From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs
Springer,
2024
Article (heidecker2024criteria)
Heidecker, F.; El-Khateeb, A.; Bieshaar, M. & Sick, B.
Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation
arXiv e-prints,
2024, arXiv:2404.11266
Inproceedings (magnussen2024optical)
Magnussen, B. M.; Möckel, F.; Jessulat, M.; Stern, C. & Sick, B.
Optical Detection of the Body Mass Index and Related Parameters Using Multiple Spatially Resolved Reflection Spectroscopy
IEEE,
2024
Inproceedings (assenmacher2023towards)
Aßenmacher, M.; Rauch, L.; Goschenhofer, J.; Stephan, A.; Bischl, B.; Roth, B. & Sick, B.
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering
2023, 65-73
Inproceedings (breitenstein2023what)
Breitenstein, J.; Heidecker, F.; Lyssenko, M.; Bogdoll, D.; Bieshaar, M.; Zöllner, J. M.; Sick, B. & Fingscheidt, T.
What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving
2023, 3991-4000
Inproceedings (decke2023dado)
Decke, J.; Gruhl, C.; Rauch, L. & Sick, B.
DADO – Low-Cost Query Strategies for Deep Active Design Optimization
IEEE,
2023, 1611-1618
Article (deinzer2023it)
Deinzer, R.; Eidenhardt, Z.; Sohrabi, K.; Stenger, M.; Kraft, D.; Sick, B.; Götz-Hahn, F.; Bottenbruch, C.; Berneburg, N. & Weik, U.
It is the habit not the handle that affects tooth brushing. Results of a randomised counterbalanced cross over study
Research Square,
2023
Inproceedings (heidecker2023context)
Heidecker, F.; Susetzky, T.; Fuchs, E. & Sick, B.
Context Information for Corner Case Detection in Highly Automated Driving
IEEE,
2023, 1522-1529
Article (heidecker2023corner)
Heidecker, F.; Bieshaar, M. & Sick, B.
Corner Cases in Machine Learning Processes
AI Perspectives & Advances,
2023, 6, 1-17
Inproceedings (huang2023spatio)
Huang, Z.; He, Y. & Sick, B.
Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction
IEEE,
2023
Article (magnussen2023continuous)
Magnussen, B. M.; Stern, C. & Sick, B.
Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent Features
International Journal On Advances in Intelligent Systems,
ThinkMind,
2023, 16, 43-50
Inproceedings (magnussen2023leveraging)
Magnussen, B. M.; Stern, C. & Sick, B.
Leveraging Repeated Unlabelled Noisy Measurements to Augment Supervised Learning
ACM,
2023, 1-6
Article (nivarthi2023multi)
Nivarthi, C. P.; Vogt, S. & Sick, B.
Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions
Machine Learning and Knowledge Extraction (MAKE),
MDPI,
2023, 5, 1214-1233
Inproceedings (nivarthi2023towards)
Nivarthi, C. P. & Sick, B.
Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding
IEEE,
2023, 1444-1450
Inproceedings (schreck2023height)
Schreck, S.; Reichert, H.; Hetzel, M.; Doll, K. & Sick, B.
Height Change Feature Based Free Space Detection
IEEE,
2023, 171-176
Article (schreiber2023model)
Schreiber, J. & Sick, B.
Model selection, adaptation, and combination for transfer learning in wind and photovoltaic power forecasts
Energy and AI,
2023, 14, 100249
Article (loeser2022vision)
Loeser, I.; Braun, M.; Gruhl, C.; Menke, J.-H.; Sick, B. & Tomforde, S.
The Vision of Self-Management in Cognitive Organic Power Distribution Systems
Energies,
MDPI,
2022, 15, 881
Article (pham2022stream)
Pham, T.; Kottke, D.; Krempl, G. & Sick, B.
Stream-based active learning for sliding windows under the influence of verification latency
Machine Learning,
Springer,
2022, 111, 2011-2036