Co-Diffusion: An Affinity-Aware Two-Stage Latent Diffusion Framework for Generalizable Drug-Target Affinity Prediction
arXiv 2603.11125•32dd1141ab900cae1d25cef3271859cb8f48bc1763a3f1d81d5d46eb1d4924c9
L^p-approximationMEEReLU-networksVAEapproximation-theorybfVAEcalibrationcontextual-bandits','exploration','RIE-Greedy','regularization-2deep-learningdiagnostic-transport-mapsdisentanglementdrug-discoverydrug-target-affinityforecastinginterpretabilitylatent-diffusionlatent-traversalmachine-learningminimum-error-entropynonparametric-regressionrare-eventstheorytropical-cyclone-forecastinguncertainty-quantificationzero-shot-generalization
Paper metadata
- arXiv ID
- 2603.11125
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- 32dd1141ab900cae1d25cef3271859cb8f48bc1763a3f1d81d5d46eb1d4924c9
- Enrichment time
- 2026-03-13T07:24:00Z
- AI-assisted enrichment
- Yes
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