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Charles B. Delahunt
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2020 – today
- 2024
- [i11]Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning:
Driving down Poisson error can offset classification error in clinical tasks. CoRR abs/2405.06065 (2024) - 2023
- [c8]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:
Deep Learning Video Classification of Lung Ultrasound Features Associated with Pneumonia. CVPR Workshops 2023: 3103-3112 - [c7]Menghan Yu
, Sourabh Kulhare
, Courosh Mehanian, Charles B. Delahunt, Daniel E. Shea, Zohreh Laverriere, Ishan Shah, Matthew P. Horning:
How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound. SASHIMI@MICCAI 2023: 75-85 - [i10]Menghan Yu, Sourabh Kulhare, Courosh Mehanian, Charles B. Delahunt, Daniel E. Shea, Zohreh Laverriere, Ishan Shah, Matthew P. Horning:
How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound. CoRR abs/2310.03608 (2023) - 2022
- [j4]Charles B. Delahunt
, J. Nathan Kutz
:
A Toolkit for Data-Driven Discovery of Governing Equations in High-Noise Regimes. IEEE Access 10: 31210-31234 (2022) - [j3]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:
PySINDy: A comprehensive Python package for robust sparse system identification. J. Open Source Softw. 7(69): 3994 (2022) - [i9]Charles B. Delahunt, Noni Gachuhi, Matthew P. Horning:
Use case-focused metrics to evaluate machine learning for diseases involving parasite loads. CoRR abs/2209.06947 (2022) - 2021
- [i8]Charles B. Delahunt, J. Nathan Kutz:
A toolkit for data-driven discovery of governing equations in high-noise regimes. CoRR abs/2111.04870 (2021) - [i7]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:
PySINDy: A comprehensive Python package for robust sparse system identification. CoRR abs/2111.08481 (2021) - 2020
- [c6]Charles B. Delahunt, Wenbo Wang
, Simon Ghionea, Andrew Miller, Austin Chan, Anjali Sehrawat, Courosh Mehanian, Michael Friend:
Algorithms to predict moisture content of grain using relative humidity time-series. GHTC 2020: 1-8 - [i6]Shawn K. McGuire, Charles B. Delahunt:
Predicting United States policy outcomes with Random Forests. CoRR abs/2008.07338 (2020)
2010 – 2019
- 2019
- [j2]Charles B. Delahunt, J. Nathan Kutz:
Putting a bug in ML: The moth olfactory network learns to read MNIST. Neural Networks 118: 54-64 (2019) - [c5]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:
Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images. GHTC 2019: 1-8 - [i5]Charles B. Delahunt, Courosh Mehanian, J. Nathan Kutz:
Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy. CoRR abs/1901.09283 (2019) - [i4]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:
Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information. CoRR abs/1908.01901 (2019) - 2018
- [j1]Charles B. Delahunt, Jeffrey A. Riffell, J. Nathan Kutz:
Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, With Applications to Neural Nets. Frontiers Comput. Neurosci. 12: 102 (2018) - [c4]Charles B. Delahunt, J. Nathan Kutz:
A moth brain learns to read MNIST. ICLR (Workshop) 2018 - [i3]Charles B. Delahunt, Jeffrey A. Riffell, J. Nathan Kutz:
Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, with Applications to Neural Nets. CoRR abs/1802.02678 (2018) - [i2]Charles B. Delahunt, J. Nathan Kutz:
Putting a bug in ML: The moth olfactory network learns to read MNIST. CoRR abs/1802.05405 (2018) - [i1]Charles B. Delahunt, J. Nathan Kutz:
Insect cyborgs: Biological feature generators improve machine learning accuracy on limited data. CoRR abs/1808.08124 (2018) - 2017
- [c3]Courosh Mehanian, Mayoore S. Jaiswal, Charles B. Delahunt, Clay Thompson, Matthew P. Horning, Liming Hu, Shawn K. McGuire, Travis Ostbye, Martha Mehanian, Benjamin K. 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:
Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks. ICCV Workshops 2017: 116-125 - 2015
- [c2]Charles B. Delahunt, Courosh Mehanian, Liming Hu, Shawn K. McGuire, Cary R. Champlin, Matthew P. Horning, Benjamin K. Wilson, Clay M. Thompson:
Automated microscopy and machine learning for expert-level malaria field diagnosis. GHTC 2015: 393-399 - 2012
- [c1]Katie O'Leary, Charles B. Delahunt, Patricia Dowden, Ivan Darmansya, Jiaqi Heng, Eve A. Riskin, Richard E. Ladner
, Jacob O. Wobbrock:
Design goals for a system for enhancing AAC with personalized video. ASSETS 2012: 223-224
Coauthor Index
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last updated on 2024-08-05 21:25 CEST by the dblp team
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