{FlashGraph}: Processing {Billion-Node} graphs on an array of commodity {SSDs} D Zheng, D Mhembere, R Burns, J Vogelstein, CE Priebe, AS Szalay 13th USENIX Conference on File and Storage Technologies (FAST 15), 45-58, 2015 | 293 | 2015 |
MIGRAINE: MRI graph reliability analysis and inference for connectomics WG Roncal, ZH Koterba, D Mhembere, DM Kleissas, JT Vogelstein, ... 2013 IEEE Global Conference on Signal and Information Processing, 313-316, 2013 | 56 | 2013 |
A high-throughput pipeline identifies robust connectomes but troublesome variability G Kiar, EW Bridgeford, WRG Roncai, ... Biorxiv, 188706, 2017 | 48* | 2017 |
Semi-external memory sparse matrix multiplication for billion-node graphs D Zheng, D Mhembere, V Lyzinski, JT Vogelstein, CE Priebe, R Burns IEEE Transactions on Parallel and Distributed Systems 28 (5), 1470-1483, 2016 | 29 | 2016 |
Forest packing: Fast parallel, decision forests J Browne, D Mhembere, TM Tomita, JT Vogelstein, R Burns Proceedings of the 2019 SIAM International Conference on Data Mining, 46-54, 2019 | 25 | 2019 |
Computing scalable multivariate glocal invariants of large (brain-) graphs D Mhembere, WG Roncal, D Sussman, CE Priebe, R Jung, S Ryman, ... 2013 IEEE Global Conference on Signal and Information Processing, 297-300, 2013 | 23 | 2013 |
ndmg: Neurodata’s mri graphs pipeline G Kiar, WG Roncal, D Mhembere, E Bridgeford, R Burns, J Vogelstein Zenodo, 2016 | 20 | 2016 |
knor: a NUMA-optimized in-memory, distributed and semi-external-memory k-means library D Mhembere, D Zheng, CE Priebe, JT Vogelstein, R Burns Proceedings of the 26th International Symposium on High-Performance Parallel …, 2017 | 10 | 2017 |
FlashMatrix: parallel, scalable data analysis with generalized matrix operations using commodity SSDs D Zheng, D Mhembere, JT Vogelstein, CE Priebe, R Burns arXiv preprint arXiv:1604.06414 9, 30, 2016 | 6 | 2016 |
FlashR: parallelize and scale R for machine learning using SSDs D Zheng, D Mhembere, JT Vogelstein, CE Priebe, R Burns Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of …, 2018 | 5 | 2018 |
A high-throughput pipeline identifies robust connectomes but troublesome variability. bioRxiv, 188706 G Kiar, EW Bridgeford, WR Gray Roncal, V Chandrashekhar, ... submitted for publication, 2018 | 5 | 2018 |
clusterNOR: A NUMA-Optimized Clustering Framework D Mhembere, D Zheng, CE Priebe, JT Vogelstein, R Burns arXiv preprint arXiv:1902.09527, 2019 | 4 | 2019 |
A low-resource reliable pipeline to democratize multi-modal connectome estimation and analysis J Chung, R Lawrence, A Loftus, D Pisner, G Kiar, EW Bridgeford, ... bioRxiv, 2021.11. 01.466686, 2021 | 3 | 2021 |
Graphyti: a semi-external memory graph library for FlashGraph D Mhembere, D Zheng, CE Priebe, JT Vogelstein, R Burns arXiv preprint arXiv:1907.03335, 2019 | 2 | 2019 |
Massive diffusion mri graph structure preserves spatial information DL Sussman, D Mhembere, S Ryman, R Jung, RJ Vogelstein, R Burns, ... Organization for Human Brain Mapping, 2013 | 1 | 2013 |
Scalable Graph Analysis and Clustering on Commodity Hardware DN Mhembere Johns Hopkins University, 2019 | | 2019 |
Feature Clustering from a Brain Graph for Voxel-to-Region Classification N Sismanis, DL Sussman, JT Vogelstein, W Gray, RJ Vogelstein, ... | | |
A Comprehensive Cloud Framework for Scalable, Reliable, and Replicable Human Connectome Es-timation and Meganalysis G Kiar, WRG Roncal, V Chandrashekhar, EW Bridgeford, D Mhembere, ... | | |