Taedong Yun
Authored Publications
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Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction
Babak Behsaz
Zachary Ryan Mccaw
Davin Hill
Robert Luben
Dongbing Lai
John Bates
Howard Yang
Tae-Hwi Schwantes-An
Yuchen Zhou
Anthony Khawaja
Andrew Carroll
Brian Hobbs
Michael Cho
Nature Genetics (2024)
Improving variant calling using population data and deep learning
Nae-Chyun Chen
Sidharth Goel
Andrew Carroll
BMC Bioinformatics (2023)
Evaluating unsupervised disentangled representations for genomic discovery and disease risk prediction
ICML Workshop on Computational Biology 2023 (2023)
Improving variant calling using population data and deep learning
Andrew Carroll
Nae-Chyun Chen
Sidharth Goel
BMC Bioinformatics (2023)
DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer
Aaron Wenger
Andrew Walker Carroll
Armin Töpfer
Ashish Teku Vaswani
Daniel Cook
Felipe Llinares
Gunjan Baid
Howard Cheng-Hao Yang
Jean-Philippe Vert
Kishwar Shafin
Maria Nattestad
Waleed Ammar
William J. Rowell
Nature Biotechnology (2022)
How DeepConsensus Works
Aaron Wenger
Anastasiya Belyaeva
Andrew Carroll
Armin Töpfer
Ashish Teku Vaswani
Daniel Cook
Felipe Llinares
Gunjan Baid
Howard Yang
Jean-Philippe Vert
Kishwar Shafin
Maria Nattestad
Waleed Ammar
William J. Rowell
(2022)
DeepNull models non-linear covariate effects to improve phenotypic prediction and association power
Andrew Carroll
Babak Alipanahi
Zachary Ryan Mccaw
Nick Furlotte
Nature Communications (2022)
DeepNull models non-linear covariate effects to improve phenotypic prediction and association power
Zachary R. Mccaw
Nicholas A. Furlotte
Andrew Carroll
Babak Alipanahi
Nature Communications (2022)
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
Steve Yadlowsky
Advances in Neural Information Processing Systems (2021)
Accurate, scalable cohort variant calls using DeepVariant and GLnexus
Helen Li
Michael F. Lin
Andrew Walker Carroll
Bioinformatics (2021)
