Figure 1. Schematic diagram of the overall workflow of physical embedding machine learning force field: including high-order isovariant models, physical knowledge-guided adaptive bond length sampling ...

Dimension reduction plays a crucial role in machine learning to serve data exploration and visualization 1,2. By transforming data into an embedding space, it reveals the intrinsic structures and ...

Parameterisation schemes within General Circulation Models are required to capture cloud processes and precipitation formation but exhibit long-standing known biases. Here, we develop a hybrid ...