257 citations · 543 across the 14 of their papers we have counts for
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cs.LG2022★ 6 cited
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science
Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales +2
We present the Open MatSci ML Toolkit: a flexible, self-contained, and scalable Python-based framework to apply deep learning models and methods on scientific data with a specific…
cs.LG2022★ 2 cited
Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design
Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp +2
Being able to predict the performance of circuits without running expensive simulations is a desired capability that can catalyze automated design. In this paper, we present a supe…