Marco Bagatella

According to our database, Marco Bagatella authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Zero-Shot Offline Imitation Learning via Optimal Transport.

Thomas Rupf, Marco Bagatella, Nico Gürtler, Jonas Frey, Georg Martius

CoRR, 2024

Active Fine-Tuning of Generalist Policies.

Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause

CoRR, 2024

Directed Exploration in Reinforcement Learning from Linear Temporal Logic.

Marco Bagatella, Andreas Krause, Georg Martius

CoRR, 2024

Causal Action Influence Aware Counterfactual Data Augmentation.

Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica, Georg Martius

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Modelling Microbial Communities with Graph Neural Networks.

Albane Ruaud, Cansu Sancaktar, Marco Bagatella, Christoph Ratzke, Georg Martius

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Goal-conditioned Offline Planning from Curious Exploration.

Marco Bagatella, Georg Martius

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Learning of High Level Plans from Play.

Núria Armengol Urpí, Marco Bagatella, Otmar Hilliges, Georg Martius, Stelian Coros

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning.

Marco Bagatella, Sammy Joe Christen, Otmar Hilliges

Trans. Mach. Learn. Res., 2022

TempoRL: Temporal Priors for Exploration in Off-Policy Reinforcement Learning.

Marco Bagatella, Sammy Joe Christen, Otmar Hilliges

CoRR, 2022

2021

Planning from Pixels in Environments with Combinatorially Hard Search Spaces.

Marco Bagatella, Miroslav Olsák, Michal Rolínek, Georg Martius

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021