2 papers
cs.LG2026
Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation
Peidong Liu, Wenbo Zhang, Wei Ju +2
The paradigm shift toward structure-driven molecule generation has been propelled by advances in deep generative models, such as variational auto-encoders and diffusion models. How…
cs.CV2025
Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generation
Wenhao Zheng, Chenwei Sun, Wenbo Zhang +2
Deep generative models, such as diffusion models, have shown promising progress in image generation and audio generation via simplified continuity assumptions. However, the develop…