Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

Two important architectures are Artificial Neural Networks and Long Short-Term Memory networks. LSTM networks are especially useful for financial applications because they are designed to work with ...

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

For many diseases and chronic conditions, an individual's genes play a role in their likelihood of developing the disease. While some inherited diseases, such as cystic fibrosis or sickle cell anemia, ...

In recent decades researchers have shown that an adolescent’s neurobiology and environment interact to shape emotional and behavioral development, but to date this work has struggled to capture the ...

The chapters of “Machine Learning Methods for Engineering Application Development“ book are organized into five parts Machine Learning Essentials, Applied Machine Learning, Surveillance Systems, ...

In materials science, substances are often classified based on defining factors such as their elemental composition or ...