Before revision:  Contrary to existing models like DeepNovo or DeepMatch which represents each spectrum as a long sparse vector, in DeepNovoV2, we propose to directly represent a spectrum as a set of (m/z, intensity) pairs . Then we use an order invariant network structure (T-Net) to extract features from the spectrum.
After revision:  Contrary to existing models like DeepNovo or DeepMatch which represents each spectrum as a long sparse vector, in DeepNovoV2, we propose to directly represent a spectrum as a set of (m/z, intensity) pairs , therefore it does not suffer from the accuracy-speed/memory trade-off problem. The model combines an order invariant network structure (T-Net) to extract features from the spectrum.