A non-linear activation function. q λ = q i or q ij , Q Predicted atom or bond target value (unconstrained), and expected net value for molecule M . φ(x), ν, δ, n, y Radial basis function of scalar x, three associated parameters, and output vector y. f λ Learned FFNN embedding of atom or bond. k λ , w λ Attention mechanism parameters. q final λ Final overall molecular constraint-corrected predicted target value. a.k.a. nodes) and bonds as edges (E, a.k.a. links), and F (n) is a tensor that carries various node, edge, and graph attributes. The encoding of a molecular graph in Chemprop begins with the initialization of nodes and edges with features based on the structural topology of the molecule being represented and the chemical identities of the corresponding atoms and bonds. More specifically, the default atom features, α α α chem,i , consist of atomic number, formal charge, chirality, hybridization, aromaticity, total number of bonds and hydrogens to which an atom is connected, and scaled atomic mass. The default bond features, β β β chem,ij , consist of bond order, the presence of conjugation or ring structures, and stereochemical information such as cis/trans isomerism. We added functionality in Chemprop to include additional QM descriptors in the initial feature vectors, and thus: