Stephanie L Hyland
Stephanie L Hyland
PhD Student, Weill Cornell/Memorial Sloan Kettering Cancer Center
Verified email at cornell.edu - Homepage
Title
Cited by
Cited by
Year
Real-valued (medical) time series generation with recurrent conditional gans
C Esteban, SL Hyland, G Rätsch
arXiv preprint arXiv:1706.02633, 2017
1862017
Identification of active transcriptional regulatory elements from GRO-seq data
CG Danko, SL Hyland, LJ Core, AL Martins, CT Waters, HW Lee, ...
Nature methods 12 (5), 433-438, 2015
1212015
Neural document embeddings for intensive care patient mortality prediction
P Grnarova, F Schmidt, SL Hyland, C Eickhoff
arXiv preprint arXiv:1612.00467, 2016
352016
Learning Unitary Operators with Help From u (n)
SL Hyland, G Rätsch
AAAI 2017, 2016
272016
Improving clinical predictions through unsupervised time series representation learning
X Lyu, M Hueser, SL Hyland, G Zerveas, G Rätsch
arXiv preprint arXiv:1812.00490, 2018
122018
Real-valued (medical) time series generation with recurrent conditional gans
S Hyland, C Esteban, G Rätsch
112018
A generative model of words and relationships from multiple sources
SL Hyland, T Karaletsos, G Rätsch
Association for the Advancement of Artificial Intelligence, 2016
62016
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs (2017)
C Esteban, SL Hyland, G Rätsch
URL http://arxiv. org/abs, 1811
61811
Early prediction of circulatory failure in the intensive care unit using machine learning
SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ...
Nature Medicine 26 (3), 364-373, 2020
52020
Real-valued (medical) time series generation with recurrent conditional GANs. arXiv 2017
C Esteban, SL Hyland, G Rätsch
arXiv preprint arXiv:1706.02633, 0
5
Machine learning for early prediction of circulatory failure in the intensive care unit
SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ...
arXiv preprint arXiv:1904.07990, 2019
42019
On the Intrinsic Privacy of Stochastic Gradient Descent
SL Hyland, S Tople
arXiv preprint arXiv:1912.02919, 2019
22019
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies
SG Stark, SL Hyland, MF Pradier, K Lehmann, A Wicki, FP Cruz, JE Vogt, ...
arXiv preprint arXiv:1904.12973, 2019
22019
Knowledge transfer with medical language embeddings
SL Hyland, T Karaletsos, G Rätsch
arXiv preprint arXiv:1602.03551, 2016
22016
Largescale sentence clustering from electronic health records for genetic associations in cancer
MF Pradier, S Stark, S Hyland, JE Vogt, G Rätsch
Machine Learning for Computational Biology Workshop in Neural Information …, 2015
22015
Predicting circulatory system deterioration in intensive care unit patients.
SL Hyland, M Hüser, X Lyu, M Faltys, T Merz, G Rätsch
AIH@ IJCAI, 87-92, 2018
12018
Accurate identification of active transcriptional regulatory elements from global run-on and sequencing data
CG Danko, SL Hyland, LJ Core, AL Martins, CT Waters, HW Lee, ...
BioRxiv, 011353, 2014
12014
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit
E Rocheteau, P Liò, S Hyland
arXiv preprint arXiv:2007.09483, 2020
2020
Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks
E Rocheteau, P Liò, S Hyland
arXiv preprint arXiv:2006.16109, 2020
2020
A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer Types
MF Pradier, SL Hyland, SG Stark, K Lehmann, JE Vogt, F Perez-Cruz, ...
ETH Zurich, 2019
2019
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