110 citations · 208 across the 8 of their papers we have counts for
8 papers
DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
Rulin Shao, Akari Asai, Shannon Zejiang Shen +18
Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are trained on easily verifiable short-form…
Subgraph Neural Networks
Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li +1
Deep learning methods for graphs achieve remarkable performance on many node-level and graph-level prediction tasks. However, despite the proliferation of the methods and their suc…
ML4H Abstract Track 2019
Matthew B. A. McDermott, Emily Alsentzer, Sam Finlayson +5
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) workshop at NeurIPS 2019. This index is not complete, as some accepted abstracts chose to opt-out…
Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles
Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering +2
Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property predic…
Towards generative adversarial networks as a new paradigm for radiology education
Samuel G. Finlayson, Hyunkwang Lee, Isaac S. Kohane +1
Medical students and radiology trainees typically view thousands of images in order to "train their eye" to detect the subtle visual patterns necessary for diagnosis. Nevertheless,…
Privacy-Preserving Distributed Deep Learning for Clinical Data
Brett K. Beaulieu-Jones, William Yuan, Samuel G. Finlayson +1
Deep learning with medical data often requires larger samples sizes than are available at single providers. While data sharing among institutions is desirable to train more accurat…