Publications

Tim Bakker, Fabio Valerio Massoli, Thomas Hehn, Tribhuvanesh Orekondy, Arash Behboodi (2023). Switching policies for solving inverse problems. NeurIPS Deep Inverse Workshop 2023.

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Tim Bakker, Thomas Hehn, Tribhuvanesh Orekondy, Arash Behboodi, Fabio Valerio Massoli (2023). Active Learning Policies for Solving Inverse Problems. NeurIPS ReALML Workshop 2023.

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Tim Bakker, Herke van Hoof, Max Welling (2023). Learning objective-specific active learning strategies with Attentive Neural Processes. ECML 2023.

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Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forre (2022). E-Valuating Classifier Two-Sample Tests. TMLR 2024.

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Tim Bakker, Matthew Muckley, Adriana Romero-Soriano, Michal Drozdzal, Luis Pineda (2022). On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. MIDL 2022.

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Sierk Kanis, Laurens Samson, Daan Bloembergen, Tim Bakker (2021). Back to Basics: Deep Reinforcement Learning in Traffic Signal Control. UrbComp 2021, Best Paper Award runner-up.

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Tim Bakker, Herke van Hoof, Max Welling (2020). Experimental design for MRI by greedy policy search. NeurIPS 2020, Spotlight.

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