4 papers
scGTN: Deep Siamese Graph Transformer Network for Single-cell RNA Sequencing Clustering
Jinke Wu, Yifan Wang, Siyu Yi +5
Single-cell RNA sequencing (scRNA-seq) serves a pivotal role in characterizing gene expression at the cellular level, enabling the identification of cell types and advancing the un…
BRIDGE: Biological Evidence Refinement and Heterogeneous Dynamic Gating for Gene Regulatory Networks
Ziyang Dong, Shanwen Tan, Hengchuang Yin +5
Motivation: Gene regulatory network inference from single-cell RNA sequencing (scRNA-seq) data is important for uncovering cell-state-specific transcriptional programs. However, sc…
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…
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…