| Multiscale deconstruction of molecular architecture in corn stover H Inouye, Y Zhang, L Yang, N Venugopalan, RF Fischetti, SC Gleber, ... Scientific reports 4 (1), 3756, 2014 | 41 | 2014 |
| Reduced electron exposure for energy-dispersive spectroscopy using dynamic sampling Y Zhang, GMD Godaliyadda, N Ferrier, EB Gulsoy, CA Bouman, C Phatak Ultramicroscopy 184, 90-97, 2018 | 18 | 2018 |
| Time-based roofline for deep learning performance analysis Y Wang, C Yang, S Farrell, Y Zhang, T Kurth, S Williams 2020 IEEE/ACM Fourth Workshop on Deep Learning on Supercomputers (DLS), 10-19, 2020 | 14 | 2020 |
| Slads-net: Supervised learning approach for dynamic sampling using deep neural networks Y Zhang, GM Godaliyadda, N Ferrier, EB Gulsoy, CA Bouman, C Phatak arXiv preprint arXiv:1803.02972, 2018 | 14 | 2018 |
| Breakdown of hierarchical architecture in cellulose during dilute acid pretreatments Y Zhang, H Inouye, L Yang, ME Himmel, M Tucker, L Makowski Cellulose 22, 1495-1504, 2015 | 14 | 2015 |
| Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances Y Zhang, H Inouye, M Crowley, L Yu, D Kaeli, L Makowski Journal of Applied Crystallography 49 (6), 2244-2248, 2016 | 13 | 2016 |
| U-slads: Unsupervised learning approach for dynamic dendrite sampling Y Zhang, X Huang, N Ferrier, EB Gulsoy, C Phatak arXiv preprint arXiv:1807.02233, 2018 | 4 | 2018 |
| High performance computing of fiber scattering simulation L Yu, Y Zhang, X Gong, N Roy, L Makowski, D Kaeli Proceedings of the 8th Workshop on General Purpose Processing using GPUs, 90-98, 2015 | 4 | 2015 |
| A Molecular-MNIST dataset for machine learning study on diffraction imaging and microscopy Y Zhang, S Farrell, M Crowley, L Makowski, J Deslippe Microscopy Histopathology and Analytics, JTh2A. 28, 2020 | 3 | 2020 |
| Under-sampling and image reconstruction for scanning electron microscopes Y Zhang, GMD Godaliyadda, YSG Nashed, N Ferrier, EB Gulsoy, ... Microscopy and Microanalysis 23 (S1), 136-137, 2017 | 3 | 2017 |
| Fast simulation of X-ray diffraction patterns from cellulose fibrils using GPUs Y Zhang, L Yu, D Kaeli, L Makowski 2014 40th annual northeast bioengineering conference (NEBEC), 1-2, 2014 | 3 | 2014 |
| 3D distributed deep learning framework for prediction of human intelligence from brain MRI S Han, Y Zhang, Y Ren, J Posner, S Yoo, J Cha Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and …, 2020 | 2 | 2020 |
| Auto-thresholding Edge Detector for bio-image processing Y Zhang, L Makowski 2015 41st Annual Northeast Biomedical Engineering Conference (NEBEC), 1-2, 2015 | 2 | 2015 |
| Deep Learning, Dynamic Sampling and Smart Energy-dispersive Spectroscopy Y Zhang, GMD Godaliyadda, N Ferrier, EB Gulsoy, CA Bouman, C Phatak Frontiers in Optics, FM3C. 6, 2017 | 1 | 2017 |
| Training a Large-Scale 3D Convolutional Neural Network Predicting Human Intelligence in Adolescent Brain Cognitive Development Study S Han, Y Zhang, Y Ren, S Yoo, J Cha | | 2022 |
| Cellulose crystallinity: What does it mean? M Crowley, M Himmel, L Bu, Y Zhang, L Makowski ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 253, 2017 | | 2017 |
| A new pre-processing method for scanning X-ray microdiffraction patterns Y Zhang, J Liu, L Makowski 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-4, 2015 | | 2015 |
