10 citations · 11 across the 4 of their papers we have counts for
6 papers
spora: A Unified Multimodal Dataset and Platform for Spatial Proteomics
Benedikt von Querfurth, Johann Wenckstern, Eeshaan Jain +9
Spatial proteomics (SP) captures the molecular composition and spatial organization of tissues at single-cell resolution, opening a direct view of the cellular ecosystems that driv…
Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
Eeshaan Jain, Linus Bleistein, Bart Deplancke +1
Recent progress in multimodal, high-dimensional learning has enabled foundation models to process heterogeneous, large-scale data. However, at test time, acquiring all features or…
MTBBench: A Multimodal Sequential Clinical Decision-Making Benchmark in Oncology
Kiril Vasilev, Alexandre Misrahi, Eeshaan Jain +5
Multimodal Large Language Models (LLMs) hold promise for biomedical reasoning, but current benchmarks fail to capture the complexity of real-world clinical workflows. Existing eval…
AI-powered virtual tissues from spatial proteomics for clinical diagnostics and biomedical discovery
Johann Wenckstern, Eeshaan Jain, Yexiang Cheng +9
Spatial proteomics technologies have transformed our understanding of complex tissue architecture in cancer but present unique challenges for computational analysis. Each study use…
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal +3
Existing subset selection methods for efficient learning predominantly employ discrete combinatorial and model-specific approaches which lack generalizability. For an unseen archit…
Graph Edit Distance with General Costs Using Neural Set Divergence
Eeshaan Jain, Indradyumna Roy, Saswat Meher +2
Graph Edit Distance (GED) measures the (dis-)similarity between two given graphs, in terms of the minimum-cost edit sequence that transforms one graph to the other. However, the ex…