Can you trust your model's uncertainty? evaluating predictive uncertainty under dataset shift Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, J Dillon, ...
Advances in neural information processing systems 32, 2019
868 2019 Likelihood ratios for out-of-distribution detection J Ren, PJ Liu, E Fertig, J Snoek, R Poplin, M Depristo, J Dillon, ...
Advances in neural information processing systems 32, 2019
376 2019 VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data J Ren, NA Ahlgren, YY Lu, JA Fuhrman, F Sun
Microbiome 5 (1), 1-20, 2017
306 2017 Alignment-free NA Ahlgren, J Ren, YY Lu, JA Fuhrman, F Sun
Nucleic acids research 45 (1), 39-53, 2017
186 2017 New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing K Song, J Ren, G Reinert, M Deng, MS Waterman, F Sun
Briefings in bioinformatics 15 (3), 343-353, 2014
175 2014 Identifying viruses from metagenomic data using deep learning J Ren, K Song, C Deng, NA Ahlgren, JA Fuhrman, Y Li, X Xie, R Poplin, ...
Quantitative Biology 8 (1), 64-77, 2020
168 2020 Comparison of metagenomic samples using sequence signatures B Jiang, K Song, J Ren, M Deng, F Sun, X Zhang
BMC genomics 13 (1), 1-17, 2012
87 2012 Alignment-free sequence comparison based on next-generation sequencing reads K Song, J Ren, Z Zhai, X Liu, M Deng, F Sun
Journal of computational biology 20 (2), 64-79, 2013
78 2013 Alignment-free sequence analysis and applications J Ren, X Bai, YY Lu, K Tang, Y Wang, G Reinert, F Sun
Annual Review of Biomedical Data Science 1, 93, 2018
68 2018 Exploring the limits of out-of-distribution detection S Fort, J Ren, B Lakshminarayanan
Advances in Neural Information Processing Systems 34, 7068-7081, 2021
62 2021 Gut microbial and metabolomic profiles after fecal microbiota transplantation in pediatric ulcerative colitis patients DJ Nusbaum, F Sun, J Ren, Z Zhu, N Ramsy, N Pervolarakis, S Kunde, ...
FEMS microbiology ecology 94 (9), fiy133, 2018
56 2018 CAFE: aC celerated A lignment-F rE e sequence analysis YY Lu, K Tang, J Ren, JA Fuhrman, MS Waterman, F Sun
Nucleic acids research 45 (W1), W554-W559, 2017
55 2017 A network-based integrated framework for predicting virus–prokaryote interactions W Wang, J Ren, K Tang, E Dart, JC Ignacio-Espinoza, JA Fuhrman, ...
NAR genomics and bioinformatics 2 (2), lqaa044, 2020
44 2020 Can you trust your model’s uncertainty Y Ovadia, E Fertig, J Ren, Z Nado, D Sculley, S Nowozin, JV Dillon, ...
evaluating predictive uncertainty under dataset shift, 2019
36 2019 Prediction of virus-host infectious association by supervised learning methods M Zhang, L Yang, J Ren, NA Ahlgren, JA Fuhrman, F Sun
BMC bioinformatics 18 (3), 143-154, 2017
35 2017 Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ...
Medical Image Analysis 75, 102274, 2022
33 2022 Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics J Ren, K Song, M Deng, G Reinert, CH Cannon, F Sun
Bioinformatics 32 (7), 993-1000, 2016
31 2016 Uncertainty Baselines: Benchmarks for uncertainty & robustness in deep learning Z Nado, N Band, M Collier, J Djolonga, MW Dusenberry, S Farquhar, ...
arXiv preprint arXiv:2106.04015, 2021
27 2021 A simple fix to mahalanobis distance for improving near-ood detection J Ren, S Fort, J Liu, AG Roy, S Padhy, B Lakshminarayanan
arXiv preprint arXiv:2106.09022, 2021
26 2021 MicroPro: using metagenomic unmapped reads to provide insights into human microbiota and disease associations Z Zhu, J Ren, S Michail, F Sun
Genome biology 20 (1), 1-13, 2019
26 2019 
Fengzhu SunUniversity of Southern CaliforniaПотвърден имейл адрес: usc.edu
