11 citations · 20 across the 6 of their papers we have counts for
8 papers
Deep learning at the edge enables real-time streaming ptychographic imaging
Anakha V Babu, Tao Zhou, Saugat Kandel +15
Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from…
Real-Time Streaming and Event-driven Control of Scientific Experiments
Jakob R. Elias, Ryan Chard, Maksim Levental +3
Advancements in scientific instrument sensors and connected devices provide unprecedented insight into ongoing experiments and present new opportunities for control, optimization,…
BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes
Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka +1
Supercomputer FCFS-based scheduling policies result in many transient idle nodes, a phenomenon that is only partially alleviated by backfill scheduling methods that promote small j…
Fast and accurate learned multiresolution dynamical downscaling for precipitation
Jiali Wang, Zhengchun Liu, Ian Foster +3
This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computati…
Deep Learning-based Low-dose Tomography Reconstruction with Hybrid-dose Measurements
Ziling Wu, Tekin Bicer, Zhengchun Liu +3
Synchrotron-based X-ray computed tomography is widely used for investigating inner structures of specimens at high spatial resolutions. However, potential beam damage to samples of…
Scientific Image Restoration Anywhere
Vibhatha Abeykoon, Zhengchun Liu, Rajkumar Kettimuthu +2
The use of deep learning models within scientific experimental facilities frequently requires low-latency inference, so that, for example, quality control operations can be perform…