Flow-based generative model
Statistical model used in machine learning
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🏷️ Keywords
AbFlow (1) · Antibody design (1) · Flow matching (1) · Antigen-antibody binding (1) · Generative AI (1) · Bioinformatics (1) · Paratope (1)
📖 Key Information
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
The direct modeling of likelihood provides many advantages. For example, the negative log-likelihood can be directly computed and minimized as the loss function.
📰 Related News (1)
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🇺🇸 AbFlow : End-to-end Paratope-Centric Antibody Design by Interaction Enhanced Flow Matching
arXiv:2602.07084v1 Announce Type: cross Abstract: Antigen-antibody binding is a critical process in the immune response. Although recent progress has...
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