9 citations · 13 across the 4 of their papers we have counts for
4 papers
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness
Dacheng Li, Hongyi Wang, Eric Xing +1
Scaling up model sizes can lead to fundamentally new capabilities in many machine learning (ML) tasks. However, training big models requires strong distributed system expertise to…
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization
Zeyi Huang, Haohan Wang, Dong Huang +2
Training with an emphasis on "hard-to-learn" components of the data has been proven as an effective method to improve the generalization of machine learning models, especially in t…
Computational catalyst discovery: Active classification through myopic multiscale sampling
Kevin Tran, Willie Neiswanger, Kirby Broderick +3
The recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the f…
Methods for comparing uncertainty quantifications for material property predictions
Kevin Tran, Willie Neiswanger, Junwoong Yoon +3
Data science and informatics tools have been proliferating recently within the computational materials science and catalysis fields. This proliferation has spurned the creation of…