Underspecification Presents Challenges for Credibility in Modern Machine Learning

Alexander D’Amour, Katherine Heller, Dan Moldovan, +37

arXiv (Cornell University)

Artificial IntelligenceEngineeringMachine LearningModern Ml PipelinesMachine Learning Tool +15

Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Taedong Yun, Helen Li, Pi-Chuan Chang, +3

Bioinformatics

DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer

Gunjan Baid, Daniel E. Cook, Kishwar Shafin, +16

Nature Biotechnology

Sequence ModellingEngineeringMachine LearningComputer EngineeringGap-aware Sequence Transformer +7

A population-specific reference panel for improved genotype imputation in African Americans

Jared O’Connell, Taedong Yun, Meghan E. Moreno, +54

Communications Biology

Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Taedong Yun, Helen Li, Pi-Chuan Chang, +3

BioinformaticsTool GlnexusGeneticsGenomes ProjectMedicine +13

DeepNull models non-linear covariate effects to improve phenotypic prediction and association power

Zachary R. McCaw, Thomas Colthurst, Taedong Yun, +5

Nature Communications

GeneticsGenetic EpidemiologyStatistical PowerGenome-wide Association StudiesGenome-wide Association Study +16

DeepTrio: Variant Calling in Families Using Deep Learning

Alexey Kolesnikov, Sidharth Goel, Maria Nattestad, +6

Structured PredictionEngineeringMachine LearningGeneticsGenomics +17

Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction

Taedong Yun, Justin Cosentino, Babak Behsaz, +14

Nature Genetics

Improving variant calling using population data and deep learning

Nae-Chyun Chen, Alexey Kolesnikov, Sidharth Goel, +3

BMC Bioinformatics

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Gunjan Baid, Daniel E. Cook, Kishwar Shafin, +15

Pacbio HifiEngineeringGeneticsGenomicsSequence Alignment +22