Matthias Hüser

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All published works

Action	Title	Year	Authors
+	Early prediction of respiratory failure in the intensive care unit.	2021	Matthias Hüser Martin Faltys Xinrui Lyu Chris Barber Stephanie L. Hyland Tobias M. Merz Gunnar Rätsch
+	Neighborhood Contrastive Learning Applied to Online Patient Monitoring	2021	Hugo Yèche Gideon Dresdner Francesco Locatello Matthias Hüser Gunnar Rätsch
+	HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data	2021	Hugo Yèche Rita Kuznetsova Marc Zimmermann Matthias Hüser Xinrui Lyu Martin Faltys Gunnar Rätsch
+	Early prediction of respiratory failure in the intensive care unit	2021	Matthias Hüser Martin Faltys Xinrui Lyu Chris Barber Stephanie L. Hyland Tobias M. Merz Gunnar Rätsch
+	WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU.	2020	Jonathan Heitz Joanna Ficek Martin Faltys Tobias M. Merz Gunnar Rätsch Matthias Hüser
+	WRSE -- a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU	2020	Jonathan Heitz Joanna Ficek Martin Faltys Tobias M. Merz Gunnar Rätsch Matthias Hüser
+ PDF Chat	Forecasting intracranial hypertension using multi-scale waveform metrics	2019	Matthias Hüser Adrian Kündig Walter Karlen Valéria De Luca Martin Jaggi
+	Machine learning for early prediction of circulatory failure in the intensive care unit	2019	Stephanie L. Hyland Martin Faltys Matthias Hüser Xinrui Lyu Thomas Gumbsch Cristóbal Esteban Christian Bock Max Horn Michael Moor Bastian Rieck
+	DPSOM: Deep Probabilistic Clustering with Self-Organizing Maps	2019	Laura Manduchi Matthias Hüser Julia E. Vogt Gunnar Rätsch Vincent Fortuin
+	Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series	2018	Vincent Fortuin Matthias Hüser Francesco Locatello Heiko Strathmann Gunnar Rätsch
+	SOM-VAE: Interpretable Discrete Representation Learning on Time Series	2018	Vincent Fortuin Matthias Hüser Francesco Locatello Heiko Strathmann Gunnar Rätsch
+	Improving Clinical Predictions through Unsupervised Time Series Representation Learning	2018	Xinrui Lyu Matthias Hüser Stephanie L. Hyland George Zerveas Gunnar Rätsch
+	SOM-VAE: Interpretable Discrete Representation Learning on Time Series	2018	Vincent Fortuin Matthias Hüser Francesco Locatello Heiko Strathmann Gunnar Rätsch

Common Coauthors

Coauthor	Papers Together
Gunnar Rätsch	12
Martin Faltys	6
Xinrui Lyu	5
Tobias M. Merz	5
Vincent Fortuin	4
Francesco Locatello	4
Stephanie L. Hyland	4
Heiko Strathmann	3
Marc Zimmermann	2
Joanna Ficek	2
Jonathan Heitz	2
Hugo Yèche	2
Chris Barber	2
George Zerveas	1
Cristóbal Esteban	1
Valéria De Luca	1
Julia E. Vogt	1
Christian Bock	1
Gideon Dresdner	1
Thomas Gumbsch	1
Walter Karlen	1
Rita Kuznetsova	1
Dean A. Bodenham	1
Martin Jaggi	1
Karsten Borgwardt	1
Bastian Rieck	1
Max Horn	1
Michael Moor	1
Laura Manduchi	1
Adrian Kündig	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	2
+	RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism	2016	Edward Choi Mohammad Taha Bahadori Jimeng Sun Joshua A. Kulas Andy Schuetz Walter F. Stewart	2
+	Consistent Individualized Feature Attribution for Tree Ensembles.	2018	Scott Lundberg Gabriel Erion Su‐In Lee	2
+	Nonparametric Estimation from Incomplete Observations	1992	Edward L. Kaplan Paul Meier	1
+ PDF Chat	Bag-of-words representation for biomedical time series classification	2013	Jin Wang Ping Liu Mary She Saeid Nahavandi Abbas Z. Kouzani	1
+	The Lognormal Distribution as a Model for Survival Time in Cancer, With an Emphasis on Prognostic Factors	2001	Patrick Royston	1
+	The Lorenz attractor exists	1999	Warwick Tucker	1
+	Combining parametric, semi-parametric, and non-parametric survival models with stacked survival models	2015	Andrew Wey John Connett Kyle Rudser	1
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	1
+ PDF Chat	Deterministic Nonperiodic Flow	1963	Edward N. Lorenz	1
+	Discriminative Unsupervised Feature Learning with Convolutional Neural Networks	2014	Alexey Dosovitskiy Jost Tobias Springenberg Martin Riedmiller Thomas Brox	1
+ PDF Chat	Representation Learning: A Review and New Perspectives	2013	Yoshua Bengio Aaron Courville P. M. Durai Raj Vincent	1
+	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems	2016	Martı́n Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Gregory S. Corrado Andy Davis Jay B. Dean Matthieu Devin	1
+	InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	2016	Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel	1
+	Multi-task Prediction of Disease Onsets from Longitudinal Lab Tests	2016	Narges Razavian Jake Marcus David Sontag	1
+ PDF Chat	Unsupervised Pretraining for Sequence to Sequence Learning	2017	Prajit Ramachandran Peter Liu Quoc V. Le	1
+	Canonical Correlation Analysis for Analyzing Sequences of Medical Billing Codes	2016	Corinne L. Jones Sham M. Kakade Lucas W. Thornblade David R. Flum Abraham D. Flaxman	1
+	The Use of Autoencoders for Discovering Patient Phenotypes	2017	Harini Suresh Peter Szolovits Marzyeh Ghassemi	1
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	1
+	Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs	2017	Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch	1
+	Consistent feature attribution for tree ensembles	2017	Scott Lundberg Su‐In Lee	1
+	Identifying Similar Patients Using Self-Organising Maps: A Case Study on Type-1 Diabetes Self-care Survey Responses	2015	Santosh Tirunagari Norman Poh Guosheng Hu David Windridge	1
+	Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms	2017	Xiao Han Kashif Rasul Roland Vollgraf	1
+	Predicting Severe Sepsis Using Text from the Electronic Health Record.	2017	Phil Culliton Michael Levinson Alice Ehresman Joshua Wherry Jay S. Steingrub Stephen I. Gallant	1
+	Deep Unsupervised Clustering Using Mixture of Autoencoders	2017	Dejiao Zhang Yifan Sun Brian Eriksson Laura Balzano	1
+	Clustering with Deep Learning: Taxonomy and New Methods	2018	Elie Aljalbout Vladimir Golkov Yawar Siddiqui Daniel Cremers	1
+	Recurrent Neural Network-Based Semantic Variational Autoencoder for Sequence-to-Sequence Learning	2018	Myeongjun Jang Seungwan Seo Pilsung Kang	1
+ PDF Chat	DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks	2018	Changhee Lee William R. Zame Jinsung Yoon Mihaela van der Schaar	1
+	Modeling Progression Free Survival in Breast Cancer with Tensorized Recurrent Neural Networks and Accelerated Failure Time Models	2017	Yinchong Yang Peter A. Fasching Volker Tresp	1
+	An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling	2018	Shaojie Bai J. Zico Kolter Vladlen Koltun	1
+	Disease-Atlas: Navigating Disease Trajectories with Deep Learning	2018	Bryan Lim Mihaela van der Schaar	1
+	Hierarchical Disentangled Representations	2018	Babak Esmaeili Hao Wu Sarthak Jain N. Siddharth Brooks Paige Jan-Willem van de Meent	1
+ PDF Chat	A scalable discrete-time survival model for neural networks	2019	Michael F. Gensheimer Balasubramanian Narasimhan	1
+	Structured Disentangled Representations	2018	Babak Esmaeili Hao Wu Sarthak Jain Alican Bozkurt N. Siddharth Brooks Paige Dana H. Brooks Jennifer Dy Jan-Willem van de Meent	1
+ PDF Chat	Improving palliative care with deep learning	2018	Anand Avati Kenneth Jung Stephanie Harman N. Lance Downing Andrew Y. Ng Nigam H. Shah	1
+	Competitive Training of Mixtures of Independent Deep Generative Models	2018	Francesco Locatello Damien Vincent Ilya Tolstikhin Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf	1
+	Temporal Quilting for Survival Analysis	2019	Chang‐Hee Lee William R. Zame Ahmed M. Alaa Mihaela van der Schaar	1
+	Distributed Representations of Sentences and Documents	2014	Quoc V. Le Tomáš Mikolov	1
+	Sequence to Sequence Learning with Neural Networks	2014	Ilya Sutskever Oriol Vinyals Quoc V. Le	1
+	Distributed Representations of Words and Phrases and their Compositionality	2013	Tomáš Mikolov Ilya Sutskever Kai Chen Greg S. Corrado Jay B. Dean	1
+	Sequence-to-Sequence Models Can Directly Translate Foreign Speech	2017	Ron J. Weiss Jan Chorowski Navdeep Jaitly Yonghui Wu Zhifeng Chen	1
+	SOM-VAE: Interpretable Discrete Representation Learning on Time Series	2018	Vincent Fortuin Matthias Hüser Francesco Locatello Heiko Strathmann Gunnar Rätsch	1
+	TensorFlow: A system for large-scale machine learning	2016	Martı́n Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jay B. Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard	1
+	Neural Discrete Representation Learning	2017	Aäron van den Oord Oriol Vinyals Koray Kavukcuoglu	1
+	Ask Me Anything: Dynamic Memory Networks for Natural Language Processing	2015	Ankit Kumar Ozan İrsoy Peter Ondrúška Mohit Iyyer James Bradbury Ishaan Gulrajani Victor W. Zhong Romain Paulus Richard Socher	1
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	1
+	Continuous and Discrete-Time Survival Prediction with Neural Networks	2019	Håvard Kvamme Ørnulf Borgan	1
+	Effective Ways to Build and Evaluate Individual Survival Distributions	2020	Humza Haider Bret Hoehn S. Lindsey Davis Russell Greiner	1
+ PDF Chat	DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning	2019	Benjamin Shickel Tyler J. Loftus Lasith Adhikari Tezcan Ozrazgat‐Baslanti Azra Bihorac Parisa Rashidi	1
+ PDF Chat	Random survival forests	2008	Hemant Ishwaran Udaya B. Kogalur Eugene H. Blackstone Michael S. Lauer	1