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To get a full understanding of your problem, one would like to know what approximately the $n$-features are. Whether, it is about the geometrical structure, protein is described by a graph, where vertices correspond to atoms and edges to bonds within them - I would consider use of GraphNN, there is some research, that has demonstrated the success of GraphNN ...


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This is the task of so-called V&L (vision and language models) which effectively encode information from both worlds. There are also many training corpora covering this field already. Here is a quite recent paper on this: https://www.researchgate.net/publication/354617904_What_Vision-Language_Models_See'_when_they_See_Scenes


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An MLP is just a fully-connected feedforward neural net. In PointNet, a shared MLP means that you are applying the exact same MLP to each point in the point cloud. Think of a CNN's convolutional layer. There you apply the exact same filter at all locations, and hence the filter weights are shared or tied. If they were not shared, you'd have potentially ...


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