4 citations · 10 across the 10 of their papers we have counts for
7 papers · 1 filter
MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data
Xingzhi Sun, João Felipe Rocha, Brett Phelan +11
Understanding cellular trajectories via time-resolved single-cell transcriptomics is vital for studying development, regeneration, and disease. A key challenge is inferring continu…
Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models
Chen Liu, Xingzhi Sun, Xi Xiao +8
Large language models (LLMs) achieve remarkable performance through ever-increasing parameter counts, but scaling incurs steep computational costs. To better understand LLM scaling…
STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics
Joao F. Rocha, Ke Xu, Xingzhi Sun +6
The advent of single-cell technology has significantly improved our understanding of cellular states and subpopulations in various tissues under normal and diseased conditions by e…
Principal Curvatures Estimation with Applications to Single Cell Data
Yanlei Zhang, Lydia Mezrag, Xingzhi Sun +6
The rapidly growing field of single-cell transcriptomic sequencing (scRNAseq) presents challenges for data analysis due to its massive datasets. A common method in manifold learnin…
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
Xingzhi Sun, Danqi Liao, Kincaid MacDonald +7
Rapid growth of high-dimensional datasets in fields such as single-cell RNA sequencing and spatial genomics has led to unprecedented opportunities for scientific discovery, but it…
Bayesian Formulations for Graph Spectral Denoising
Sam Leone, Xingzhi Sun, Michael Perlmutter +1
Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as…
DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms
Dhananjay Bhaskar, Xingzhi Sun, Yanlei Zhang +8
We present DYMAG, a graph neural network based on a novel form of message aggregation. Standard message-passing neural networks, which often aggregate local neighbors via mean-aggr…