2 citations · 2 across the 5 of their papers we have counts for
6 papers
NIH-MPINet: A Large-Scale Feature-Rich Network Dataset for Mapping the Frontiers of Team Science
Cuiran Shi, Shuying Han, Shreya Kusumanchi +2
This study presents a large-scale network dataset, NIH-MPINet, curated from NIH RePORTER and PubMed, characterizing collaboration among multiple Principal Investigators (multi-PIs)…
Large-scale spatial variable gene atlas for spatial transcriptomics
Jiawen Chen, Jinwei Zhang, Dongshen Peng +4
Spatial variable genes (SVGs) reveal critical information about tissue architecture, cellular interactions, and disease microenvironments. As spatial transcriptomics (ST) technolog…
The Nearest-Neighbor Derivative Process: Modeling Spatial Rates of Change in Massive Datasets
Jiawen Chen, Aritra Halder, Yun Li +2
Gaussian processes (GPs) are instrumental in modeling spatial processes, offering precise interpolation and prediction capabilities across fields such as environmental science and…
STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics
Jiawen Chen, Muqing Zhou, Wenrong Wu +3
Recent advances in multi-modal algorithms have driven and been driven by the increasing availability of large image-text datasets, leading to significant strides in various fields,…
Gaussian Processes for Time Series with Lead-Lag Effects with applications to biology data
Wancen Mu, Jiawen Chen, Eric S. Davis +4
Investigating the relationship, particularly the lead-lag effect, between time series is a common question across various disciplines, especially when uncovering biological process…
On the Identifiability and Interpretability of Gaussian Process Models
Jiawen Chen, Wancen Mu, Yun Li +1
In this paper, we critically examine the prevalent practice of using additive mixtures of Matérn kernels in single-output Gaussian process (GP) models and explore the properties of…