Heinert, E., Tilgner, S., Palm, T., & Rottmann, M. (2024). Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks.

Mack, N. A., Schümmer, F., Rose, M., & Tobias, M. (2024). "Evaluating Text Placement in Information-Rich Virtual Environments: A User Study on Controller-Anchored Text" in Nordic Conference on Human-Computer Interaction , New York, NY, USA : ACM 1—10.

Puiseau, C., Dörpelkus, C., Peters, J., Tercan, H., & Meisen, T. (2024). Beyond Training: Optimizing Reinforcement Learning Based Job Shop Scheduling Through Adaptive Action Sampling.

Puiseau, C. W. d., Wolz, F., Montag, M., Peters, J., Tercan, H., & Meisen, T. (2024). Decision Transformer for Enhancing Neural Local Search on the Job Shop Scheduling Problem.

Saini, L., Su, Y., Tercan, H., & Meisen, T. (2024). "CenterPoint Transformer for BEV Object Detection with Automotive Radar" in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops . 4451—4460.

Stillger, F., Hasecke, F., & Meisen, T. (2024). Principal Component Clustering for Semantic Segmentation in Synthetic Data Generation.

Tousside, B., Frochte, J., & Meisen, T. (2024). "CNNs Sparsification and Expansion for Continual Learning" in Proceedings of the 16th International Conference on Agents and Artificial Intelligence , SciTePress - Science and and Technology Publications 110—120.

Weiss, M., Brierley, N., Schmid, M., & Meisen, T. (2024). "Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography" , NDT , 2 (1), 1—15.

Weiss, M., Brierley, N., Schmid, M., & Meisen, T. (2024). "End-To-End Deep Learning Material Discrimination Using Dual-Energy LINAC-CT" , e-Journal of Nondestructive Testing , 29 (3),

Weiss, M., & Meisen, T. (2024). "Reviewing Material-Sensitive Computed Tomography: From Handcrafted Algorithms to Modern Deep Learning" , NDT , 2 (3), 286—310.

Alves Gomes, M., & Meisen, T. (2023). "A review on customer segmentation methods for personalized customer targeting in e-commerce use cases" , Information Systems and e-Business Management , 21 (3), 527—570.

Alves Gomes, M., Wönkhaus, M., Meisen, P., & Meisen, T. (2023). "TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior" , Journal of Theoretical and Applied Electronic Commerce Research , 18 (3), 1404—1418.

Braken, R., Paulus, A., Pomp, A., & Meisen, T. (2023). "An Evaluation of Link Prediction Approaches in Few-Shot Scenarios" , Electronics , 12 (10), 2296.

Bulow, F., & Meisen, T. (2023). "A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions" , Journal of Energy Storage , 57 , 105978.

Bulow, F., Hahn, Y., Meyes, R., & Meisen, T. (2023). "Transparent and Interpretable State of Health Forecasting of Lithium-Ion Batteries with Deep Learning and Saliency Maps" , International Journal of Energy Research , 2023 ,