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Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing


Jan 11, 2023
Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Perez-Garcia, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay

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* Currently under peer-review 

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Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions


Mar 08, 2021
Maximilian Ilse, Patrick Forré, Max Welling, Joris M. Mooij

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Problems using deep generative models for probabilistic audio source separation


Nov 03, 2020
Maurice Frank, Maximilian Ilse

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* 1st I Can't Believe It's Not Better Workshop (ICBINB @ NeurIPS 2020), Vancouver, Canada 

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Designing Data Augmentation for Simulating Interventions


May 06, 2020
Maximilian Ilse, Jakub M. Tomczak, Patrick Forré

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DIVA: Domain Invariant Variational Autoencoders


May 24, 2019
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

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Attention-based Deep Multiple Instance Learning


Jun 28, 2018
Maximilian Ilse, Jakub M. Tomczak, Max Welling

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* ICML 2018 paper, code source: https://github.com/AMLab-Amsterdam/AttentionDeepMIL 

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Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification


Dec 05, 2017
Jakub M. Tomczak, Maximilian Ilse, Max Welling

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* Workshop on "Medical Imaging meets NIPS" at NIPS 2017 

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