Researchers from BIFOLD and Google DeepMind have developed MD-ET, a transformer-based molecular dynamics model that omits traditional physics constraints like energy conservation and equivariance.
Researchers at Carnegie Mellon University have developed a molecular machine learning representation that integrates stereoelectronic data from quantum chemistry, enabling faster and more accurate ...
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