Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

In recent years, with the public availability of AI tools, more people have become aware of how closely the inner workings of ...

In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is ...

Star 167 Code Issues Pull requests [ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients deep-learning model-compression ...

Designing, building, and applying new technologies—especially those that include artificial intelligence—can be a double-edged sword: powerful and enabling on the one hand, but potentially biased and ...

Eventually, global SDD maps for 2020 were produced using Landsat Operational Land Imager (OLI) TOA imagery, with SDD changing range from 0.01 to 13.1 m (mean =3.3 m). The machine learning models in ...

Dense pollution maps are essential for understanding and reducing air pollution. However, pollution measurements are often sparse. Common methods to address this gap are chemistry transport models ...

Opinion New Interactive Map Showcases Personalized Learning in All 50 States Hammonds & Hite: The adoption of policies to support competency-based teaching & learning marks a significant shift in how ...

1 School of Biomedical Engineering, Sichuan University, Chengdu, China 2 National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China ...

SchNetPack is a toolbox for the development and application of deep neural networks to the prediction of potential energy surfaces and other quantum-chemical properties of molecules and materials. It ...

Transportation is the key context ingredient in modern life. Optimised route prediction is the vital aspect for commercial enterprises and individuals also. Proper route prediction not only helps to ...