57 citations · 476 across the 23 of their papers we have counts for
3 papers · 1 filter
Learning Neural PDE Solvers with Parameter-Guided Channel Attention
Makoto Takamoto, Francesco Alesiani, Mathias Niepert
Scientific Machine Learning (SciML) is concerned with the development of learned emulators of physical systems governed by partial differential equations (PDE). In application doma…
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
Makoto Takamoto, Timothy Praditia, Raphael Leiteritz +4
Machine learning-based modeling of physical systems has experienced increased interest in recent years. Despite some impressive progress, there is still a lack of benchmarks for Sc…
An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation
Makoto Takamoto, Yusuke Morishita, Hitoshi Imaoka
Compressing deep neural network (DNN) models becomes a very important and necessary technique for real-world applications, such as deploying those models on mobile devices. Knowled…