A real-time capable force calculation algorithm for redundant tendon-based parallel manipulators. - Lars Mikelsons; Tobias Bruckmann; Manfred Hiller; Dieter Schramm (ICRA, 2008)

Towards Virtual Validation of ECU Software using FMI. - Lars Mikelsons; Roland Samlaus (Modelica, 2017)

Using the Distributed Co-Simulation Protocol for a Mixed Real-Virtual Prototype. - Peter Baumann; Martin Krammer; Mario Driussi; Lars Mikelsons; Josef Zehetner; Werner Mair; Dieter Schramm (ICM, 2019)

Towards virtual validation of distributed functions. - Peter Baumann; Roland Samlaus; Lars Mikelsons; Thomas Kuhn 001; Jasmin Jahic (SummerSim, 2019)

A simulation based interaction analysis of automated vehicles. - Lennart Luttkus; Lars Mikelsons; Peter Baumann; Oliver Kotte (SummerSim, 2019)

Learning Normalizing Flow Policies Based on Highway Demonstrations. - Damian Boborzi; Christoph-Nikolas Straehle; Jens S. Buchner; Lars Mikelsons (ITSC, 2021)

Learning to Drive from Observations while Staying Safe. - Damian Boborzi; Florian Kleinicke; Jens S. Buchner; Lars Mikelsons (IV Workshops, 2021)

NeuralFMU: Towards Structural Integration of FMUs into Neural Networks. - Tobias Thummerer; Josef Kircher; Lars Mikelsons (CoRR, 2021)

Hybrid modeling of the human cardiovascular system using NeuralFMUs. - Tobias Thummerer; Johannes Tintenherr; Lars Mikelsons (CoRR, 2021)

NeuralFMU: Presenting a workflow for integrating hybrid NeuralODEs into real world applications. - Tobias Thummerer; Johannes Stoljar; Lars Mikelsons (CoRR, 2022)

Towards Reliable Parameter Extraction in MEMS Final Module Testing Using Bayesian Inference. - Monika Elisabeth Heringhaus; Yi Zhang 139; André Zimmermann; Lars Mikelsons (Sensors, 2022)

Solving Stochastic Inverse Problems with Stochastic BayesFlow. - Yi Zhang 139; Lars Mikelsons (AIM, 2023)

Key Requirements for Autonomous Micromobility Vehicle Simulators. - Lennart Luttkus; Lars Mikelsons (SMC, 2023)

Eigen-informed NeuralODEs: Dealing with stability and convergence issues of NeuralODEs. - Tobias Thummerer; Lars Mikelsons (CoRR, 2023)

Sensitivity-guided iterative parameter identification and data generation with BayesFlow and PELS-VAE for model calibration. - Yi Zhang 139; Lars Mikelsons (Adv. Model. Simul. Eng. Sci., 2023)

Imitation learning by state-only distribution matching. - Damian Boborzi; Christoph-Nikolas Straehle; Jens S. Buchner; Lars Mikelsons (Appl. Intell., 2023)

IMFlow: Inverse Modeling with Conditional Normalizing Flows for Data-Driven Model Predictive Control. - Yi Zhang 139; Lars Mikelsons (CDC, 2024)

Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention. - Tobias Demmler; Andreas Tamke; Thao Dang 002; Karsten Haug; Lars Mikelsons (IV, 2024)

Perspectives-Observer-Transparency - A Novel Paradigm for Modelling the Human in Human-To-Anything Interaction Based on a Structured Review of the Human Digital Twin. - Nils Mandischer; Alexander Atanasyan; Michael Schluse; Jürgen Roßmann; Lars Mikelsons (SMC, 2024)

Exploring Capability-Based Control Distributions of Human-Robot Teams Through Capability Deltas: Formalization and Implications. - Nils Mandischer; Marcel Usai; Frank Flemisch; Lars Mikelsons (SMC, 2024)

Analyzing the coupling process of distributed mixed real-virtual prototypes. - Peter Baumann; Lars Mikelsons; Oliver Kotte; Dieter Schramm (CoRR, 2024)

Learnable & Interpretable Model Combination in Dynamic Systems Modeling. - Tobias Thummerer; Lars Mikelsons (CoRR, 2024)

InsertDiffusion: Identity Preserving Visualization of Objects through a Training-Free Diffusion Architecture. - Phillip Mueller; Jannik Wiese; Ioan Craciun; Lars Mikelsons (CoRR, 2024)

Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception. - Phillip Mueller; Lars Mikelsons (CoRR, 2024)

GeoBiked: A Dataset with Geometric Features and Automated Labeling Techniques to Enable Deep Generative Models in Engineering Design. - Phillip Mueller; Sebastian Mueller; Lars Mikelsons (CoRR, 2024)

Towards human capability estimation to enhance human-robot team performance. - Nils Mandischer; Lars Mikelsons (Autom., 2024)

Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations. - Julius Aka; Johannes Brunnemann; Jörg Eiden; Arne Speerforck; Lars Mikelsons (ICLR, 2025)

MeshFleet: Filtered and Annotated 3D Vehicle Dataset for Domain Specific Generative Modeling. - Damian Boborzi; Phillip Mueller; Jonas Emrich; Dominik Schmid 002; Sebastian Mueller; Lars Mikelsons (CoRR, 2025)

Dynamic Intent Queries for Motion Transformer-based Trajectory Prediction. - Tobias Demmler; Lennart Hartung; Andreas Tamke; Thao Dang 002; Alexander Hegai; Karsten Haug; Lars Mikelsons (CoRR, 2025)

Masked Conditioning for Deep Generative Models. - Phillip Mueller; Jannik Wiese; Sebastian Mueller; Lars Mikelsons (CoRR, 2025)

Beyond Features: How Dataset Design Influences Multi-Agent Trajectory Prediction Performance. - Tobias Demmler; Jakob Häringer; Andreas Tamke; Thao Dang 002; Alexander Hegai; Lars Mikelsons (CoRR, 2025)

Conjugated Capabilities: Interrelations of Elementary Human Capabilities and Their Implication on Human-Machine Task Allocation and Capability Testing Procedures. - Nils Mandischer; Larissa Füller; Torsten Alles; Frank Flemisch; Lars Mikelsons (CoRR, 2025)

Holistic Specification of the Human Digital Twin: Stakeholders, Users, Functionalities, and Applications. - Nils Mandischer; Alexander Atanasyan; Ulrich Dahmen; Michael Schluse; Jürgen Rossmann; Lars Mikelsons (CoRR, 2025)