Charles B. Delahunt

25 papers A 1Journal 16Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond validation loss: Clinically-tailored optimization metrics improve a model's clinical performance. CoRR Charles B. Delahunt, Courosh Mehanian, Daniel E. Shea, Matthew P. Horning
2024	J	`jnl`	Driving down Poisson error can offset classification error in clinical tasks. CoRR Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning
2024	—	`conf`	Reducing Poisson error can offset classification error: a technique to meet clinical performance requirements. ML4H@NeurIPS Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning
2023	—	`conf`	Deep Learning Video Classification of Lung Ultrasound Features Associated with Pneumonia. CVPR Workshops Daniel E. Shea, Sourabh Kulhare, Rachel Millin, Zohreh Laverriere, Courosh Mehanian, Charles B. Delahunt, Dipayan Banik, Xinliang Zheng, Meihua Zhu, Ye Ji, Travis Ostbye, Martha-Marie S. Mehanian, Atinuke Uwajeh, Adeseye M. Akinsete, Fen Wang, Matthew P. Horning
2023	—	`conf`	How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound. SASHIMI@MICCAI Menghan Yu, Sourabh Kulhare, Courosh Mehanian, Charles B. Delahunt, Daniel E. Shea, Zohreh Laverriere, Ishan Shah, Matthew P. Horning
2023	J	`jnl`	How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound. CoRR Menghan Yu, Sourabh Kulhare, Courosh Mehanian, Charles B. Delahunt, Daniel E. Shea, Zohreh Laverriere, Ishan Shah, Matthew P. Horning
2022	J	`jnl`	A Toolkit for Data-Driven Discovery of Governing Equations in High-Noise Regimes. IEEE Access Charles B. Delahunt, J. Nathan Kutz
2022	J	`jnl`	PySINDy: A comprehensive Python package for robust sparse system identification. J. Open Source Softw. Alan A. Kaptanoglu, Brian de Silva, Urban Fasel, Kadierdan Kaheman, Andy Goldschmidt, Jared Callaham, Charles B. Delahunt, Zachary Nicolaou, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton
2022	J	`jnl`	Use case-focused metrics to evaluate machine learning for diseases involving parasite loads. CoRR Charles B. Delahunt, Noni Gachuhi, Matthew P. Horning
2021	J	`jnl`	A toolkit for data-driven discovery of governing equations in high-noise regimes. CoRR Charles B. Delahunt, J. Nathan Kutz
2021	J	`jnl`	PySINDy: A comprehensive Python package for robust sparse system identification. CoRR Alan A. Kaptanoglu, Brian M. de Silva, Urban Fasel, Kadierdan Kaheman, Jared L. Callaham, Charles B. Delahunt, Kathleen P. Champion, Jean-Christophe Loiseau, J. Nathan Kutz, Steven L. Brunton
2020	—	`conf`	Algorithms to predict moisture content of grain using relative humidity time-series. GHTC Charles B. Delahunt, Wenbo Wang, Simon Ghionea, Andrew Miller, Austin Chan, Anjali Sehrawat, Courosh Mehanian, Michael Friend
2020	J	`jnl`	Predicting United States policy outcomes with Random Forests. CoRR Shawn K. McGuire, Charles B. Delahunt
2019	J	`jnl`	Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information. CoRR Charles B. Delahunt, Mayoore S. Jaiswal, Matthew P. Horning, Samantha Janko, Clay M. Thompson, Sourabh Kulhare, Liming Hu, Travis Ostbye, Grace Yun, Roman Gebrehiwot, Benjamin K. Wilson, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell, Courosh Mehanian
2019	—	`conf`	Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images. GHTC Charles B. Delahunt, Roman Gebrehiwot, Benjamin K. Wilson, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Mayoore S. Jaiswal, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell, Courosh Mehanian, Matthew P. Horning, Samantha Janko, Clay M. Thompson, Sourabh Kulhare, Liming Hu, Travis Ostbye, Grace Yun
2019	J	`jnl`	Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy. CoRR Charles B. Delahunt, Courosh Mehanian, J. Nathan Kutz
2019	J	`jnl`	Putting a bug in ML: The moth olfactory network learns to read MNIST. Neural Networks Charles B. Delahunt, J. Nathan Kutz
2018	—	`conf`	A moth brain learns to read MNIST. ICLR (Workshop) Charles B. Delahunt, J. Nathan Kutz
2018	J	`jnl`	Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets. Frontiers Comput. Neurosci. Charles B. Delahunt, Jeffrey A. Riffell, J. Nathan Kutz
2018	J	`jnl`	Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, with Applications to Neural Nets. CoRR Charles B. Delahunt, Jeffrey A. Riffell, J. Nathan Kutz
2018	J	`jnl`	Insect cyborgs: Biological feature generators improve machine learning accuracy on limited data. CoRR Charles B. Delahunt, J. Nathan Kutz
2018	J	`jnl`	Putting a bug in ML: The moth olfactory network learns to read MNIST. CoRR Charles B. Delahunt, J. Nathan Kutz
2017	—	`conf`	Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks. ICCV Workshops Courosh Mehanian, Mayoore S. Jaiswal, Charles B. Delahunt, Clay Thompson, Matthew P. Horning, Liming Hu, Shawn K. McGuire, Travis Ostbye, Martha Mehanian, Ben Wilson, Cary R. Champlin, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David Isaboke, Bernhards Ogutu, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell
2015	—	`conf`	Automated microscopy and machine learning for expert-level malaria field diagnosis. GHTC Charles B. Delahunt, Courosh Mehanian, Liming Hu, Shawn K. McGuire, Cary R. Champlin, Matthew P. Horning, Benjamin K. Wilson, Clay M. Thompson
2012	A	`conf`	Design goals for a system for enhancing AAC with personalized video. ASSETS Katie O'Leary, Charles B. Delahunt, Patricia Dowden, Ivan Darmansya, Jiaqi Heng, Eve A. Riskin, Richard E. Ladner, Jacob O. Wobbrock