Michael Moor | DeepAI

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Featured Co-authors

Jure Leskovec
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∙ 01/28/2023

Zero-shot causal learning

Predicting how different interventions will causally affect a specific i...

10 Hamed Nilforoshan, et al. ∙

∙ 07/12/2021

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

Despite decades of clinical research, sepsis remains a global public hea...

2 Michael Moor, et al. ∙

∙ 02/15/2021

Topological Graph Neural Networks

Graph neural networks (GNNs) are a powerful architecture for tackling gr...

68 Max Horn, et al. ∙

∙ 07/02/2020

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score

Randomized controlled trials typically analyze the effectiveness of trea...

0 Zhiliang Wu, et al. ∙

∙ 05/25/2020

Path Imputation Strategies for Signature Models

The signature transform is a 'universal nonlinearity' on the space of co...

10 Michael Moor, et al. ∙

∙ 09/26/2019

Set Functions for Time Series

Despite the eminent successes of deep neural networks, many architecture...

0 Max Horn, et al. ∙

∙ 06/03/2019

Topological Autoencoders

We propose a novel approach for preserving topological structures of the...

1 Michael Moor, et al. ∙

∙ 04/16/2019

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

Intensive care clinicians are presented with large quantities of patient...

0 Stephanie L. Hyland, et al. ∙

∙ 02/05/2019

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

Motivation: Sepsis is a life-threatening host response to infection asso...

0 Michael Moor, et al. ∙

∙ 12/23/2018

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

While many approaches to make neural networks more fathomable have been ...

16 Bastian Rieck, et al. ∙