Evaluating students' abilities to construct mathematical models from data using latent class analysis
Sign Up to like & getrecommendations! Published in 2018 at "Chemistry Education Research and Practice"
DOI: 10.1039/c7rp00126f
Abstract: Analyzing and interpreting data is an important science practice that contributes toward the construction of models from data; yet, there is evidence that students may struggle with making meaning of data. The study reported here… read more here.
Keywords: analysis; chemistry; latent class; rate ... See more keywords
Learning physically consistent differential equation models from data using group sparsity.
Sign Up to like & getrecommendations! Published in 2021 at "Physical review. E"
DOI: 10.1103/physreve.103.042310
Abstract: We propose a statistical learning framework based on group-sparse regression that can be used to (i) enforce conservation laws, (ii) ensure model equivalence, and (iii) guarantee symmetries when learning or inferring differential-equation models from data.… read more here.
Keywords: equation models; physically consistent; differential equation; models data ... See more keywords
On the Private Data Synthesis Through Deep Generative Models for Data Scarcity of Industrial Internet of Things
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3133625
Abstract: Due to the data-driven intelligence from the recent deep learning based approaches, the huge amount of data collected from various kinds of sensors from industrial devices have the potential to revolutionize the current technologies used… read more here.
Keywords: private data; synthesis deep; generative models; models data ... See more keywords