2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Reliable edge machine learning hardware for scientific applications
Tommaso Baldi, Javier Campos, Ben Hawks +15
Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementatio…
cond-mat.mtrl-sci2023
Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction
Ursula Ludacka, Jiali He, Shuyu Qin +9
Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials…
cs.CE2021★ 2 cited
Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations
Shen Wang, Mehdi Nikfar, Joshua C. Agar +1
Computational fluid dynamics (CFD) simulations are broadly applied in engineering and physics. A standard description of fluid dynamics requires solving the Navier-Stokes (N-S) equ…