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Lars Mikelsons
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2020 – today
- 2024
- [c10]Tobias Demmler, Andreas Tamke, Thao Dang, Karsten Haug, Lars Mikelsons:
Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention. IV 2024: 168-175 - [i10]Peter Baumann, Lars Mikelsons, Oliver Kotte, Dieter Schramm:
Analyzing the coupling process of distributed mixed real-virtual prototypes. CoRR abs/2401.11779 (2024) - [i9]Tobias Demmler, Andreas Tamke, Thao Dang, Karsten Haug, Lars Mikelsons:
Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention. CoRR abs/2405.10134 (2024) - [i8]Tobias Thummerer, Lars Mikelsons:
Learnable & Interpretable Model Combination in Dynamic Systems Modeling. CoRR abs/2406.08093 (2024) - [i7]Phillip Mueller, Jannik Wiese, Ioan Craciun, Lars Mikelsons:
InsertDiffusion: Identity Preserving Visualization of Objects through a Training-Free Diffusion Architecture. CoRR abs/2407.10592 (2024) - [i6]Phillip Mueller, Lars Mikelsons:
Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception. CoRR abs/2407.11104 (2024) - 2023
- [j3]Yi Zhang
, Lars Mikelsons:
Sensitivity-guided iterative parameter identification and data generation with BayesFlow and PELS-VAE for model calibration. Adv. Model. Simul. Eng. Sci. 10(1): 9 (2023) - [j2]Damian Boborzi
, Christoph-Nikolas Straehle, Jens S. Buchner, Lars Mikelsons:
Imitation learning by state-only distribution matching. Appl. Intell. 53(24): 30865-30886 (2023) - [c9]Yi Zhang
, Lars Mikelsons:
Solving Stochastic Inverse Problems with Stochastic BayesFlow. AIM 2023: 966-972 - [c8]Lennart Luttkus, Lars Mikelsons:
Key Requirements for Autonomous Micromobility Vehicle Simulators. SMC 2023: 1506-1511 - [i5]Tobias Thummerer, Lars Mikelsons:
Eigen-informed NeuralODEs: Dealing with stability and convergence issues of NeuralODEs. CoRR abs/2302.10892 (2023) - 2022
- [j1]Monika Elisabeth Heringhaus
, Yi Zhang
, André Zimmermann
, Lars Mikelsons:
Towards Reliable Parameter Extraction in MEMS Final Module Testing Using Bayesian Inference. Sensors 22(14): 5408 (2022) - [i4]Damian Boborzi, Christoph-Nikolas Straehle, Jens S. Buchner, Lars Mikelsons:
Imitation Learning by State-Only Distribution Matching. CoRR abs/2202.04332 (2022) - [i3]Tobias Thummerer, Johannes Stoljar, Lars Mikelsons:
NeuralFMU: Presenting a workflow for integrating hybrid NeuralODEs into real world applications. CoRR abs/2209.03933 (2022) - 2021
- [c7]Damian Boborzi, Christoph-Nikolas Straehle, Jens S. Buchner, Lars Mikelsons:
Learning Normalizing Flow Policies Based on Highway Demonstrations. ITSC 2021: 22-29 - [c6]Damian Boborzi, Florian Kleinicke, Jens S. Buchner, Lars Mikelsons:
Learning to Drive from Observations while Staying Safe. IV Workshops 2021: 160-167 - [i2]Tobias Thummerer, Josef Kircher, Lars Mikelsons:
NeuralFMU: Towards Structural Integration of FMUs into Neural Networks. CoRR abs/2109.04351 (2021) - [i1]Tobias Thummerer, Johannes Tintenherr, Lars Mikelsons:
Hybrid modeling of the human cardiovascular system using NeuralFMUs. CoRR abs/2109.04880 (2021)
2010 – 2019
- 2019
- [c5]Peter Baumann, Martin Krammer, Mario Driussi, Lars Mikelsons, Josef Zehetner, Werner Mair, Dieter Schramm
:
Using the Distributed Co-Simulation Protocol for a Mixed Real-Virtual Prototype. ICM 2019: 440-445 - [c4]Peter Baumann, Roland Samlaus, Lars Mikelsons, Thomas Kuhn, Jasmin Jahic:
Towards virtual validation of distributed functions. SummerSim 2019: 5:1-5:12 - [c3]Lennart Luttkus, Lars Mikelsons, Peter Baumann, Oliver Kotte:
A simulation based interaction analysis of automated vehicles. SummerSim 2019: 6:1-6:11 - 2017
- [c2]Lars Mikelsons, Roland Samlaus:
Towards Virtual Validation of ECU Software using FMI. Modelica 2017: 132:033
2000 – 2009
- 2008
- [c1]Lars Mikelsons, Tobias Bruckmann
, Manfred Hiller, Dieter Schramm
:
A real-time capable force calculation algorithm for redundant tendon-based parallel manipulators. ICRA 2008: 3869-3874
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last updated on 2024-08-25 19:11 CEST by the dblp team
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