102 citations · 650 across the 27 of their papers we have counts for
5 papers · 1 filter
Reducing the Long Tail Losses in Scientific Emulations with Active Learning
Yi Heng Lim, Muhammad Firmansyah Kasim
Deep-learning-based models are increasingly used to emulate scientific simulations to accelerate scientific research. However, accurate, supervised deep learning models require hug…
A feasibility study of using X-ray Thomson Scattering to diagnose the in-flight plasma conditions of DT cryogenic implosions
H. Poole, D. Cao, R. Epstein +9
The design of inertial confinement fusion (ICF) ignition targets requires radiation-hydrodynamics simulations with accurate models of the fundamental material properties (i.e., equ…
DQC: a Python program package for Differentiable Quantum Chemistry
Muhammad F. Kasim, Susi Lehtola, Sam M. Vinko
Automatic differentiation represents a paradigm shift in scientific programming, where evaluating both functions and their derivatives is required for most applications. By removin…
Failure modes and downtime of radiotherapy linear accelerators and Multi-Leaf Collimators in Indonesia
Gregory S. Peiris, Supriyanto A. Pawiro, Muhammad F. Kasim +1
The lack of equitable access to radiotherapy linear accelerators (LINACs) is a substantial barrier to cancer care in Low and Middle-Income Countries (LMICs). Aside from the issue o…
Learning the exchange-correlation functional from nature with fully differentiable density functional theory
Muhammad F. Kasim, Sam M. Vinko
Improving the predictive capability of molecular properties in ab initio simulations is essential for advanced material discovery. Despite recent progress making use of machine lea…