"Our workflow employs a unique strategy where machine learning models first predict the most probable space groups and crystal densities, filtering out unstable, low-density candidates before ...

How much time is your machine learning team spending on labeling data — and how much of that data is actually improving model performance? Creating effective training data is a challenge that many ML ...

Researchers have developed a machine-learning workflow to optimize the output force of photo-actuated organic crystals. Using LASSO regression to identify key molecular substructures and Bayesian ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...