Markus Peschl

13 papers A* 2A 1B 1C 1Journal 8
YearRankTypeTitle / Venue / Authors
2025 A* conf
Differentiable and Learnable Wireless Simulation with Geometric Transformers.
ICLR
Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer
2025 J jnl
Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action models.
CoRR
Rokas Bendikas, Daniel Dijkman, Markus Peschl, Sanjay Haresh, Pietro Mazzaglia
2025 J jnl
From Code to Action: Hierarchical Learning of Diffusion-VLM Policies.
CoRR
Markus Peschl, Pietro Mazzaglia, Daniel Dijkman
2025 J jnl
Hybrid Training for Vision-Language-Action Models.
CoRR
Pietro Mazzaglia, Cansu Sancaktar, Markus Peschl, Daniel Dijkman
2024 J jnl
NeuroSteiner: A Graph Transformer for Wirelength Estimation.
CoRR
Sahil Manchanda, Dana Kianfar, Markus Peschl, Romain Lepert, Michaël Defferrard
2024 J jnl
Probabilistic and Differentiable Wireless Simulation with Geometric Transformers.
CoRR
Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer
2023 A* conf
Robust Scheduling with GFlowNets.
ICLR
David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan
2023 J jnl
Robust Scheduling with GFlowNets.
CoRR
David W. Zhang, Corrado Rainone, Markus Peschl, Roberto Bondesan
2022 B conf
Learning Perturbations for Soft-Output Linear MIMO Demappers.
GLOBECOM
Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan
2022 J jnl
Learning Perturbations for Soft-Output Linear MIMO Demappers.
CoRR
Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan
2022 A conf
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning.
AAMAS
Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert
2022 J jnl
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning.
CoRR
Markus Peschl, Arkady Zgonnikov, Frans A. Oliehoek, Luciano Cavalcante Siebert
2021 C conf
Training for Implicit Norms in Deep Reinforcement Learning Agents through Adversarial Multi-Objective Reward Optimization.
AIES
Markus Peschl