6 papers
LATTICE: Graph Self-Supervised Learning for Multimodal Spatial Omics Integration
Jagan Mohan Reddy Dwarampudi, Veena Kochat, Suresh Satpati +3
Spatially resolved omics studies increasingly combine transcriptomic and epigenomic assays, yet downstream analysis is often still performed using single-modality pipelines. We pre…
CDS: Counterfactual Directionality Score for Structured Interventions in Spatial Graphs
Humaira Anzum, Md Ishtyaq Mahmud, Jagan Mohan Reddy Dwarampudi +1
Quantifying directional influence between node populations is a fundamental problem in graph-based modeling, particularly in spatial biological systems where cell-cell interactions…
A Reproducible Framework for Bias-Resistant Machine Learning on Small-Sample Neuroimaging Data
Jagan Mohan Reddy Dwarampudi, Jennifer L Purks, Joshua Wong +2
We introduce a reproducible, bias-resistant machine learning framework that integrates domain-informed feature engineering, nested cross-validation, and calibrated decision-thresho…
A Multi-scale Linear-time Encoder for Whole-Slide Image Analysis
Jagan Mohan Reddy Dwarampudi, Joshua Wong, Hien Van Nguyen +1
We introduce Multi-scale Adaptive Recurrent Biomedical Linear-time Encoder (MARBLE), the first \textit{purely Mamba-based} multi-state multiple instance learning (MIL) framework fo…
hSNMF: Hybrid Spatially Regularized NMF for Image-Derived Spatial Transcriptomics
Md Ishtyaq Mahmud, Veena Kochat, Suresh Satpati +4
High-resolution spatial transcriptomics platforms, such as Xenium, generate single-cell images that capture both molecular and spatial context, but their extremely high dimensional…
Benchmarking Dimensionality Reduction Techniques for Spatial Transcriptomics
Md Ishtyaq Mahmud, Veena Kochat, Suresh Satpati +3
We introduce a unified framework for evaluating dimensionality reduction techniques in spatial transcriptomics beyond standard PCA approaches. We benchmark six methods PCA, NMF, au…