Michael Moor

According to our database, Michael Moor authored at least 17 papers between 2018 and 2023.

Collaborative distances:

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

2023

Zero-shot causal learning.

Hamed Nilforoshan, Michael Moor, Yusuf Roohani, Yining Chen, Anja Surina, Michihiro Yasunaga, Sara Oblak, Jure Leskovec

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

Med-Flamingo: a Multimodal Medical Few-shot Learner.

Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, Pranav Rajpurkar

Proceedings of the Machine Learning for Health, 2023

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting.

Benjamin Yan, Ruochen Liu, David E. Kuo, Subathra Adithan, Eduardo Pontes Reis, Stephen Kwak, Vasantha Kumar Venugopal, Chloe O'Connell, Agustina Saenz, Pranav Rajpurkar, Michael Moor

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Machine Learning on Clinical Time Series: Classification and Representation Learning.

Michael Moor

PhD thesis, 2022

Topological Graph Neural Networks.

Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A Survey of Topological Machine Learning Methods.

Felix Hensel, Michael Moor, Bastian Rieck

Frontiers Artif. Intell., 2021

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning.

Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt

CoRR, 2021

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning.

Christian Bock, Michael Moor, Catherine R. Jutzeler, Karsten M. Borgwardt

Proceedings of the Artificial Neural Networks - Third Edition., 2021

2020

Path Imputation Strategies for Signature Models.

Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck

CoRR, 2020

Topological Autoencoders.

Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the 37th International Conference on Machine Learning, 2020

Set Functions for Time Series.

Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score.

Zhiliang Wu, Yinchong Yang, Yunpu Ma, Yushan Liu, Rui Zhao, Michael Moor, Volker Tresp

Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 2020

2019

Machine learning for early prediction of circulatory failure in the intensive care unit.

Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz

CoRR, 2019

Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis.

Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

CoRR, 2019

Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping.

Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

Proceedings of the Machine Learning for Healthcare Conference, 2019

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology.

Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Association mapping in biomedical time series via statistically significant shapelet mining.

Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

Bioinform., 2018