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20172026
most cited2022 Review of Data-Driven Plasma Science

85 citations · 202 across the 44 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

q-bio.BM2022

Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning

Fikret Aydin, Konstantia Georgouli, Gautham Dharuman +5

Improved understanding of the relation between the behavior of RAS and RAF proteins and the local lipid environment in the cell membrane is critical for getting insights into the m…

q-bio.QM2022

Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints

Konstantia Georgouli, Helgi I Ingólfsson, Fikret Aydin +4

Capturing intricate biological phenomena often requires multiscale modeling where coarse and inexpensive models are developed using limited components of expensive and high-fidelit…

cs.LG2022

Models Out of Line: A Fourier Lens on Distribution Shift Robustness

Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer +2

Improving the accuracy of deep neural networks (DNNs) on out-of-distribution (OOD) data is critical to an acceptance of deep learning (DL) in real world applications. It has been o…

cs.LG2022★ 9 cited

Single Model Uncertainty Estimation via Stochastic Data Centering

Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Narayanaswamy +1

We are interested in estimating the uncertainties of deep neural networks, which play an important role in many scientific and engineering problems. In this paper, we present a str…

physics.plasm-ph2022★ 22 cited

Data-driven model for divertor plasma detachment prediction

Ben Zhu, Menglong Zhao, Harsh Bhatia +5

We present a fast and accurate data-driven surrogate model for divertor plasma detachment prediction leveraging the latent feature space concept in machine learning research. Our a…

cs.HC2022★ 1 cited

"Understanding Robustness Lottery": A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches

Zhimin Li, Shusen Liu, Xin Yu +5

Deep learning approaches have provided state-of-the-art performance in many applications by relying on large and overparameterized neural networks. However, such networks have been…

physics.plasm-ph2022★ 85 cited

2022 Review of Data-Driven Plasma Science

Rushil Anirudh, Rick Archibald, M. Salman Asif +60

Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…