Total primary energy demand by fuel in China. by Da Lian (18880882)

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

“…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …”

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”

Table_1_Deep learning-based classification system of bacterial keratitis and fungal keratitis using anterior segment images.DOCX by Yeo Kyoung Won (15599561)