Samuel G. Finlayson

According to our database, Samuel G. Finlayson authored at least 12 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research.

Rulin Shao, Akari Asai, Shannon Zejiang Shen, Hamish Ivison, Varsha Kishore, Jingming Zhuo, Xinran Zhao, Molly Park, Samuel G. Finlayson, David A. Sontag, Tyler Murray, Sewon Min, Pradeep Dasigi, Luca Soldaini, Faeze Brahman, Wen-tau Yih, Tongshuang Wu, Luke Zettlemoyer, Yoon Kim, Hannaneh Hajishirzi, Pang Wei Koh

CoRR, November, 2025

2021

Code-free deep learning for multi-modality medical image classification.

Edward Korot, Zeyu Guan, Daniel Ferraz, Siegfried K. Wagner, Gongyu Zhang, Xiaoxuan Liu, Livia Faes, Nikolas Pontikos, Samuel G. Finlayson, Hagar Khalid, Gabriella Moraes, Konstantinos Balaskas, Alastair K. Denniston, Pearse A. Keane

Nat. Mach. Intell., 2021

Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles.

Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, Isaac S. Kohane

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 2021

2020

ML4H Abstract Track 2019.

Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca

CoRR, 2020

Subgraph Neural Networks.

Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning.

Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, William Yuan, Isaac S. Kohane

CoRR, 2019

Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?

Adrian V. Dalca, Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Corey Chivers, Andrew Beam, Tristan Naumann, Brett K. Beaulieu-Jones

Proceedings of the Machine Learning for Health Workshop, 2019

2018

Towards generative adversarial networks as a new paradigm for radiology education.

Samuel G. Finlayson, Hyunkwang Lee, Isaac S. Kohane, Luke Oakden-Rayner

CoRR, 2018

Privacy-Preserving Distributed Deep Learning for Clinical Data.

Brett K. Beaulieu-Jones, William Yuan, Samuel G. Finlayson, Zhiwei Steven Wu

CoRR, 2018

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018.

Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi

CoRR, 2018

Adversarial Attacks Against Medical Deep Learning Systems.

Samuel G. Finlayson, Isaac S. Kohane, Andrew L. Beam

CoRR, 2018

2016

Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data.

Samuel G. Finlayson, Mia A. Levy, Sunil Reddy, Daniel L. Rubin

J. Biomed. Informatics, 2016