Marco Bagatella
PhD student in RL, currently at the Autonomous Learning Group.
bio
I am a PhD student at MPI-IS and ETH Zürich, co-advised by Georg Martius and Andreas Krause. I am mainly interested in (deep) reinforcement learning. Previosuly, I was fortunate to spend some time at the AIT Lab (ETH Zürich), under the supervision of Prof. Otmar Hilliges, and in the Autonomous Learning Group.
Not so long ago, I obtained a MSc in Computer Science at ETH Zürich, and a few years before that I graduated from Politecnico di Milano (BSc in Engineering of Computing Systems).
research
My current main focus is on (deep) reinforcement learning, and I enjoy researching or learning about any related idea. In particular, my interests include exploration, temporal abstraction and offline approaches. In the long term, I aim to contribute to the understanding of current RL methods, and I am really excited about finding ways to tackle to rich, open-ended environments.
Outside of RL, I have some experience in representation learning and causality, and I like keeping an eye open towards other topics in machine learning or robotics.
news
Sep 22, 2023 | 🎉 Goal-conditioned Offline Planning from Curious Exploration was accepted to NeurIPS 2023 |
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May 31, 2023 | 🪧 Efficient Learning of High Level Plans from Play was presented at ICRA 2023 |
Aug 19, 2022 | 🪧 SFP (previously called TempoRL) was published in TMLR |
May 1, 2022 | 🎉 Officially starting my PhD |
Dec 16, 2021 | 🪧 Presented PPGS at NeurIPS 2021 |
selected publications
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Goal-conditioned Offline Planning from Curious ExplorationIn Advances in Neural Information Processing Systems 2023
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Efficient Learning of High Level Plans from PlayIn International Conference on Robotics and Automation 2023
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SFP: State-free Priors for Exploration in Off-Policy Reinforcement LearningTransactions on Machine Learning Research 2022
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Planning from Pixels in Environments with Combinatorially Hard Search SpacesIn Advances in Neural Information Processing Systems 2021