Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes von Würth, Tobias, Freymuth, Niklas, Zimmerling, Clemens, Neumann, Gerhard, Kärger, Luise

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Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects von Scheikl, Paul Maria, Schreiber, Nicolas, Haas, Christoph, Freymuth, Niklas, Neumann, Gerhard, Lioutikov, Rudolf, Mathis-Ullrich, Franziska

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KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty von Becker, Philipp, Freymuth, Niklas, Neumann, Gerhard

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Learning Sub-Second Routing Optimization in Computer Networks requires Packet-Level Dynamics von Boltres, Andreas, Freymuth, Niklas, Jahnke, Patrick, Karl, Holger, Neumann, Gerhard

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Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes von Würth, Tobias, Freymuth, Niklas, Zimmerling, Clemens, Neumann, Gerhard, Kärger, Luise

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Latent Task-Specific Graph Network Simulators von Dahlinger, Philipp, Freymuth, Niklas, Volpp, Michael, Hoang, Tai, Neumann, Gerhard

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Versatile Inverse Reinforcement Learning via Cumulative Rewards von Freymuth, Niklas, Becker, Philipp, Neumann, Gerhard

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Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors von Freymuth, Niklas, Schreiber, Nicolas, Becker, Philipp, Taranovic, Aleksandar, Neumann, Gerhard

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Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations von Freymuth, Niklas, Dahlinger, Philipp, Würth, Tobias, Becker, Philipp, Taranovic, Aleksandar, Grönheim, Onno, Kärger, Luise, Neumann, Gerhard

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Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards von Freymuth, Niklas, Dahlinger, Philipp, Würth, Tobias, Reisch, Simon, Kärger, Luise, Neumann, Gerhard

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Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects von Scheikl, Paul Maria, Schreiber, Nicolas, Haas, Christoph, Freymuth, Niklas, Neumann, Gerhard, Lioutikov, Rudolf, Mathis-Ullrich, Franziska

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KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty von Becker, Philipp, Freymuth, Niklas, Neumann, Gerhard

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Swarm Reinforcement Learning For Adaptive Mesh Refinement von Freymuth, Niklas, Dahlinger, Philipp, Würth, Tobias, Reisch, Simon, Kärger, Luise, Neumann, Gerhard

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Grounding Graph Network Simulators using Physical Sensor Observations von Linkerhägner, Jonas, Freymuth, Niklas, Scheikl, Paul Maria, Mathis-Ullrich, Franziska, Neumann, Gerhard

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Learning Sub-Second Routing Optimization in Computer Networks requires Packet-Level Dynamics von Boltres, Andreas, Freymuth, Niklas, Jahnke, Patrick, Karl, Holger, Neumann, Gerhard

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Bimodal Speech Emotion Recognition Using Pre-Trained Language Models von Heusser, Verena, Freymuth, Niklas, Constantin, Stefan, Waibel, Alex

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Latent Task-Specific Graph Network Simulators von Dahlinger, Philipp, Freymuth, Niklas, Volpp, Michael, Hoang, Tai, Neumann, Gerhard

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Versatile Inverse Reinforcement Learning via Cumulative Rewards von Freymuth, Niklas, Becker, Philipp, Neumann, Gerhard

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Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors von Freymuth, Niklas, Schreiber, Nicolas, Becker, Philipp, Taranovic, Aleksandar, Neumann, Gerhard

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Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations von Freymuth, Niklas, Dahlinger, Philipp, Würth, Tobias, Becker, Philipp, Taranovic, Aleksandar, Grönheim, Onno, Kärger, Luise, Neumann, Gerhard

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