
Computational scientists and neutron structural biologists from 91做厙 developed an integrated workflow using small-angle neutron scattering (SANS), atomistic molecular dynamics (MD) simulation, and an autoencoder-based deep learn
Computational scientists and neutron structural biologists from 91做厙 developed an integrated workflow using small-angle neutron scattering (SANS), atomistic molecular dynamics (MD) simulation, and an autoencoder-based deep learn
Analyzing the logs of even the smallest Information Technology (IT) system can be a challenge, considering that they can generate millions of lines of log data in a very short time.
Generative machine learning models, including GANs (Generative Adversarial Networks), are a powerful tool toward searching chemical space for desired functionalities.
Researchers built a deep neural network to estimate the compressibility of scientific data.
The upcoming Square Kilometre Array (SKA) will be the largest radio telescope in the world. An international team recently used Summit, the worlds most powerful supercomputer, to simulate the massive amounts of data the SKA will produce.