J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
C. Homs Pons, and R. Lautenschlager. Software, (2024)Related to: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models, submitted to GAMM Mitteilungen.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Dataset, (2023)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
R. Skukies. Software, (2023)Related to: Skukies, R., & Ehinger, B. V. (2023). The effect of estimation time window length on overlap correction in EEG data (2023.06.05.543689). bioRxiv. doi: 10.1101/2023.06.05.543689.
N. Schäfer, P. Tilli, T. Munz-Körner, S. Künzel, S. Vidyapu, N. Vu, and D. Weiskopf. Dataset, (2023)Related to: N. Schäfer, S. Künzel, T. Munz, P. Tilli, N. T. Vu, and D. Weiskopf. Visual Analysis of Scene-Graph-Based Visual Question Answering. Proceedings of the 16th International Symposium on Visual Information Communication and Interaction (VINCI 2023). 2023.
N. Schäfer, P. Tilli, T. Munz-Körner, S. Künzel, S. Vidyapu, N. Vu, and D. Weiskopf. Software, (2023)Related to: N. Schäfer, S. Künzel, T. Munz, P. Tilli, N. T. Vu, and D. Weiskopf. Visual Analysis of Scene-Graph-Based Visual Question Answering. Proceedings of the 16th International Symposium on Visual Information Communication and Interaction (VINCI 2023). 2023.
T. Munz-Körner, S. Künzel, and D. Weiskopf. Dataset, (2023)Related to: T. Munz-Körner, S. Künzel, and D. Weiskopf. "Visual-Explainable AI: The Use Case of Language Models". International Conference on Data-Integrated Simulation Science (SimTech2023). 2023.
F. Huber, P. Bürkner, D. Göddeke, and M. Schulte. Dataset, (2023)Related to: Huber, Felix; Bürkner, Paul-Christian; Göddeke, Dominik; Schulte, MiriamKnowledge-Based Modeling of Simulation Behavior for Bayesian OptimizationComputational Mechanics (submitted).
A. Baier, and D. Frank. Software, (2023)Related to: Baier, Alexandra, Boukhers, Zeyd, & Staab, Steffen (2021). Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction. ArXiv, abs/2103.06727. arXiv: abs/2103.06727.
A. Baier, D. Aspandi Latif, and S. Staab. Software, (2023)Related to: Alexandra Baier, Decky Aspandi and Steffen Staab, "ReLiNet: Stable and Explainable Multistep Prediction with Recurrent Linear Parameter Varying Networks", Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23), 2023.
I. Banerjee, and P. Walter. Dataset, (2022)Related to: Banerjee, I., Walter, P., Guthke, A., Mumford, K.G. & Nowak, W. (2022). The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Computational Geosciences. Accepted for publication.