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Contributions

Introducing Monge-GPs: A new class of physics-informed Gaussian Processes (extended abstract)

Introducing Monge-GPs: A new class of physics-informed Gaussian Processes (extended abstract)

  • Johanna Moser
  • Christopher Albert
  • Sascha Ranftl

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 295-298

Joint Bayesian Inference on Lagrangian Physics and Trajectories

Joint Bayesian Inference on Lagrangian Physics and Trajectories

  • Michael Obermayr
  • Robert Peharz

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 299-304

Stabilizing PINNs: A regularization scheme for PINN training to avoid unstable fixed points of dynamical systems

Stabilizing PINNs: A regularization scheme for PINN training to avoid unstable fixed points of dynamical systems

  • Miloš Babić
  • Franz Rohrhofer
  • Bernhard Geiger

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 305-313

Derivative-Enhanced Training for Data-efficient Surrogate Modeling

Derivative-Enhanced Training for Data-efficient Surrogate Modeling

  • Paul Horvath
  • Marian Staggl
  • Stefan Posch

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 314-322

Towards a PIRL framework for efficient airflow diffuser design

Towards a PIRL framework for efficient airflow diffuser design

  • Alfredo Lopez
  • Florian Sobieczky
  • Christopher Lackner
  • Matthias Hochsteger
  • Bernhard Scheichl
  • Helmuth Sobieczky
  • Christoph Feichtinger

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 323-328

Understanding the Role of Domain Knowledge in Bayesian Optimization under Small-Data Constraints

Understanding the Role of Domain Knowledge in Bayesian Optimization under Small-Data Constraints

  • Bernd Schuscha
  • Franz Rohrhofer
  • Bernhard Geiger
  • Daniel Scheiber

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 329-332

Equayes - Democratizing Probabilistic Model Construction and Exploration with automatic Equation to Bayesian Model transformation

Equayes - Democratizing Probabilistic Model Construction and Exploration with automatic Equation to Bayesian Model transformation

  • Christian Findenig
  • Manfred Mücke

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 338-342

ZeroShop: Automated Metric Mesh Generation for Zero-Shot 6D Object Pose Estimation

ZeroShop: Automated Metric Mesh Generation for Zero-Shot 6D Object Pose Estimation

  • Stefan Lechner
  • Philipp Ausserlechner
  • Markus Vincze

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 349-362

1D Profiles vs. Spectral Images: A Comparative Study of Machine Learning Models for Mineral and Rock Classification

1D Profiles vs. Spectral Images: A Comparative Study of Machine Learning Models for Mineral and Rock Classification

  • Sai Puneeth Reddy Gottam
  • Martin Johannes Findl
  • Robert Galler
  • Klaus Philipp Sedlazeck
  • Elmar Rueckert

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 363-366

Towards Recipe-driven Automation Concepts for Large-scale Food Production

Towards Recipe-driven Automation Concepts for Large-scale Food Production

  • Moritz Dorfer
  • Michael Rathmair

2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 73-76