Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026
Physics-Informed Machine Learning and Hybrid Modelling
Introducing Monge-GPs: A new class of physics-informed Gaussian Processes (extended abstract)
Johanna Moser, Christopher Albert and Sascha Ranftl
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 295-298
Joint Bayesian Inference on Lagrangian Physics and Trajectories
Michael Obermayr and Robert Peharz
2026-04-09 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
Miloš Babić, Franz Rohrhofer and Bernhard Geiger
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 305-313
Derivative-Enhanced Training for Data-efficient Surrogate Modeling
Paul Horvath, Marian Staggl and Stefan Posch
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 314-322
Towards a PIRL framework for efficient airflow diffuser design
Alfredo Lopez, Florian Sobieczky, Christopher Lackner, Matthias Hochsteger, Bernhard Scheichl, Helmuth Sobieczky and Christoph Feichtinger
2026-04-09 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
Bernd Schuscha, Franz Rohrhofer, Bernhard Geiger and Daniel Scheiber
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 329-332
Conceptual-Model-Guided Physics-Inspired Feature Engineering: A 3D-Printer Case Study
Martin Paczona
2026-06-26 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 333-337
Equayes - Democratizing Probabilistic Model Construction and Exploration with automatic Equation to Bayesian Model transformation
Christian Findenig and Manfred Mücke
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 338-342
RoboWork
Proceedings of the Robowork Workshop at AIROV 2026
Vedant Dave, Elmar Rueckert, Thomas Thurner, Siegfried Altmann and Yassine Elmanyari
2026-06-26 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 344-348
ZeroShop: Automated Metric Mesh Generation for Zero-Shot 6D Object Pose Estimation
Stefan Lechner, Philipp Ausserlechner and Markus Vincze
2026-04-09 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
Sai Puneeth Reddy Gottam, Martin Johannes Findl, Robert Galler, Klaus Philipp Sedlazeck and Elmar Rueckert
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 363-366
Spiking Neural Network Systems
SNNSys –Workshop on Spiking Neural Networks
Bernhard Moser, Michael Lunglmayr and Robert Legenstein
2026-06-26 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 368-369
Linearized Bregman Iterations for Sparse Spiking Neural Networks
Daniel Windhager, Michael Lunglmayr and Bernhard Moser
2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 370-377
Recurrent versus parallelizable spiking neural networks: A comparative study
Alexander Mayr, Simon Hitzginger and Robert Legenstein
2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 378-385
Effective Online SNN Training with One-Step Backpropagation
Saya Higuchi, Federico Corradi, Sander M. Bohté and Sebastian Otte
2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 386-391
Probabilistic LIF Neurons Improve Learning in Recurrent Spiking Neural Networks
Sebastian Higuchi, Niels A. Kloosterman, Stefan Hallermann and Sebastian Otte
2026-04-10 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 392-396
Working Memory in a Recurrent Spiking Neural Networks With Heterogeneous Synaptic Delays
Laurent Perrinet
2026-07-01 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 397-406
Semantic Scene Representations
Proceedings of the Semantic Scene Representations (SSR)Workshop at AIROV 2026
Christian Rauch, Linus Nwankwo, Shail Jadav and Jun Zhang
2026-07-01 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 408-413
Enhanced Environmental Context Encoding for Accurate Trajectory Prediction in Intralogistics
Alexander Prutsch and Horst Possegger
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 414-418
D²DINO: Dense Descriptors from DINO for Pixel‑Level Object Understanding
Paolo Sebeto, Jean-Baptiste Weibel, Christian Hartl-Nesic and Markus Vincze
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 419-428
Overcoming Nature: Perception for Autonomous Navigation in Dense Vegetation
Lukas Wimmer, Andre Koczka, Uros Petrovic and Gerald Steinbauer-Wagner
2026-04-09 Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 • 429-433