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cs.LG2026
Neural Petri flows for chemical reactions
Jose Eduardo Escrig Molina, Daniel Probst
Petri nets have been used to describe chemical processes such as reactions.They map well to chemistry: Places are the bonds between atoms and the free valence of each atom, a token…
cs.LG2026
Graph Set Transformer
Jose E. Escrig Molina, Baoquan Chen, Daniel Probst
We introduce the Graph Set Transformer (GST), a neural network architecture for learning on sets of graphs, designed for tasks in which per-element predictions depend on set-wide c…
cs.LG2025
Implicit Neural Representations of Molecular Vector-Valued Functions
Jirka Lhotka, Daniel Probst
Molecules have various computational representations, including numerical descriptors, strings, graphs, point clouds, and surfaces. Each representation method enables the applicati…