Researchers Accurately Simulate 100 Million Atoms With Machine Learning
Harvard researchers bring the accuracy, sample efficiency, and robustness of deep equivariant neural networks to the simulate 44 million atoms. This is
Brian Wang Gordon Bell Singularity University Head Of Research First Principles Dynamics Gaussian Process
Source: nextbigfuture.com