PointNovo is inspired by DeepNovo and produced by many of the same authors. PointNovo's primary innovation involves eliminating the need to discretize the spectrum m/z axis, thereby enabling the model to make use of high mass accuracy data without requiring a large memory footprint. Whereas DeepNovo uses an input vector of length 150,000 to represent a spectrum, PointNovo instead represents each spectrum as a set of (m/z, intensity) pairs. The model employs a novel architecture that is designed to handle a set of such tuples in an order-agnostic way, using ideas from the PointNet architecture . Unlike DeepNovo, the LSTM component of PointNovo is optional, though empirical results suggest that including the LSTM tends to provide higher quality predictions.