Semi-Equivariant Conditional Normalizing Flows

Eyal Rozenberg; Daniel Freedman

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arXiv · 2304.06779

Semi-Equivariant Conditional Normalizing Flows

Eyal Rozenberg·Daniel Freedman

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Abstract

We study the problem of learning conditional distributions of the form $p(G | \hat G)$, where $G$ and $\hat G$ are two 3D graphs, using continuous normalizing flows. We derive a semi-equivariance condition on the flow which ensures that conditional invariance to rigid motions holds. We demonstrate the effectiveness of the technique in the molecular setting of receptor-aware ligand generation.

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Eyal Rozenberg, Daniel Freedman. 2023-04-13. Semi-Equivariant Conditional Normalizing Flows. https://arxiv.org/abs/2304.06779

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