5 papers
HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference
Zelin Zang, WenZhe Li, Yongjie Xu +5
In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological processes. Key to this is the robust…
Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation
Changxi Chi, Jun Xia, Yufei Huang +9
Estimating single-cell responses across various perturbations facilitates the identification of key genes and enhances drug screening, significantly boosting experimental efficienc…
Beyond the Academic Monoculture: A Unified Framework and Industrial Perspective for Attributed Graph Clustering
Yunhui Liu, Yue Liu, Yongchao Liu +4
Attributed Graph Clustering (AGC) is a fundamental unsupervised task that partitions nodes into cohesive groups by jointly modeling structural topology and node attributes. While t…
GRAPE: Heterogeneous Graph Representation Learning for Genetic Perturbation with Coding and Non-Coding Biotype
Changxi Chi, Jun Xia, Jingbo Zhou +3
Predicting genetic perturbations enables the identification of potentially crucial genes prior to wet-lab experiments, significantly improving overall experimental efficiency. Sinc…
Adversarial Curriculum Graph-Free Knowledge Distillation for Graph Neural Networks
Yuang Jia, Xiaojuan Shan, Jun Xia +5
Data-free Knowledge Distillation (DFKD) is a method that constructs pseudo-samples using a generator without real data, and transfers knowledge from a teacher model to a student by…