| Learning across scales---multiscale methods for convolution neural networks E Haber, L Ruthotto, E Holtham, SH Jun Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 122 | 2018 |
| Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction X Chen, EG Sifakis, S Robertson, SY Neo, SH Jun, L Tong, AT Hui Min, ... Proceedings of the National Academy of Sciences 120 (1), e2209856120, 2023 | 14 | 2023 |
| Memory (and time) efficient sequential Monte Carlo SH Jun, A Bouchard-Côté International Conference on Machine Learning, 514-522, 2014 | 13 | 2014 |
| Inferring tumor progression in large datasets M Mohaghegh Neyshabouri, SH Jun, J Lagergren PLoS computational biology 16 (10), e1008183, 2020 | 12 | 2020 |
| Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics SH Jun, H Toosi, J Mold, C Engblom, X Chen, C O’Flanagan, ... Nature Communications 14 (1), 982, 2023 | 11* | 2023 |
| Entangled Monte Carlo SH Jun, L Wang, A Bouchard-Côté Advances in Neural Information Processing Systems 25, 2012 | 10 | 2012 |
| Boosted regression trees and random forests S Jun Statistical Consulting Report, 2013 | 9 | 2013 |
| Robust normalization and integration of single-cell protein expression across CITE-seq datasets Y Zheng, S Jun, Y Tian, M Florian, R Gottardo | 8 | 2022 |
| Scuphr: A probabilistic framework for cell lineage tree reconstruction H Koptagel, SH Jun, J Hård, J Lagergren PLOS Computational Biology 20 (5), e1012094, 2024 | 6 | 2024 |
| A topology-marginal composite likelihood via a generalized phylogenetic pruning algorithm SH Jun, H Nasif, C Jennings-Shaffer, DH Rich, A Kooperberg, ... Algorithms for Molecular Biology 18 (1), 10, 2023 | 6 | 2023 |
| Distinct immune responses associated with vaccination status and protection outcomes after malaria challenge DA Oyong, FJ Duffy, ML Neal, Y Du, J Carnes, KV Schwedhelm, ... PLoS Pathogens 19 (5), e1011051, 2023 | 5 | 2023 |
| Sequential graph matching with sequential Monte Carlo SH Jun, SWK Wong, J Zidek, A Bouchard-Côté Artificial Intelligence and Statistics, 1075-1084, 2017 | 4 | 2017 |
| Sequential decision model for inference and prediction on nonuniform hypergraphs with application to knot matching from computational forestry SH Jun, SWK Wong, JV Zidek, A Bouchard-Côté The Annals of Applied Statistics 13 (3), 1678-1707, 2019 | 3 | 2019 |
| Improved differential expression analysis of miRNA-seq data by modeling competition to be counted SH Jun, MK Halushka, MN McCall Biorxiv, 2024.05. 07.592964, 2024 | 2* | 2024 |
| 1668P Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction X Chen, EG Sifakis, S Robertson, SY Neo, SH Jun, L Tong, J Lövrot, ... Annals of Oncology 33, S1306, 2022 | | 2022 |
| Scalable sequential Monte Carlo methods and probabilistic approach to combinatorial problems SH Jun University of British Columbia, 2017 | | 2017 |
| The boosted regression trees and the random forest–DRAFT SH Jun | | 2012 |
| Formulation of fragility probabilities by logistic regression SH Jun | | 2012 |
| Supplementary Materials Scuphr: A probabilistic framework for cell lineage tree reconstruction H Koptagel, SH Jun, J Hård, J Lagergren | | |
| Generalized Pruning Algorithm SH Jun, H Nasif, F Matsen | | |
