Publications

Mague, Stephen D., Austin Talbot, Cameron Blount, Kathryn K. Walder-Christensen, Lara J. Duffney, Elise Adamson, Alexandra L. Bey, et al. “Brain-wide electrical dynamics encode individual appetitive social behavior.” Neuron 110, no. 10 (May 18, 2022): 1728-1741.e7. https://doi.org/10.1016/j.neuron.2022.02.016.

Yuan, S., Y. Li, D. Wang, K. Bai, L. Carin, and D. Carlson. “Learning to Weight Filter Groups for Robust Classification.” In Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, 3321–30, 2022. https://doi.org/10.1109/WACV51458.2022.00338.

Tu, Liyun, Austin Talbot, Neil M. Gallagher, and David E. Carlson. “Supervising the Decoder of Variational Autoencoders to Improve Scientific Utility.” IEEE Transactions on Signal Processing : A Publication of the IEEE Signal Processing Society 70 (January 2022): 5954–66. https://doi.org/10.1109/tsp.2022.3230329.

Grossman, Yael, Austin Talbot, Neil Gallagher, Gwenaëlle Thomas, Alexandra Fink, Kathryn Walder-Christensen, Scott Russo, David Carlson, and Kafui Dzirasa. “A widespread oscillatory network encodes an aggressive internal state.” BioRxiv, 2022. https://doi.org/10.1101/2022.12.07.519272.

Thornton, Luka Lila, David Carlson, and Mark Wiesner. “Predicting emerging chemical content in consumer products using machine learning.” American Chemical Society (ACS), December 21, 2021. https://doi.org/10.26434/chemrxiv-2021-96wvd.

Gallagher, Neil M., Kafui Dzirasa, and David Carlson. “Directed Spectral Measures Improve Latent Network Models Of Neural Populations.” Adv Neural Inf Process Syst 34 (December 2021): 7421–35.

Bey, Alexandra L., Kathryn K. Walder-Christensen, Jack Goffinet, Elise Adamson, Noah Lanier, Stephen D. Mague, David Carlson, and Kafui Dzirasa. “6.28 Identifying Networks Underlying Sleep Disruption in Autism Spectrum Disorder Mouse Models.” In Journal of the American Academy of Child & Adolescent Psychiatry, 60:S167–S167. Elsevier BV, 2021. https://doi.org/10.1016/j.jaac.2021.09.101.

Dunn, Timothy W., Jesse D. Marshall, Kyle S. Severson, Diego E. Aldarondo, David G. C. Hildebrand, Selmaan N. Chettih, William L. Wang, et al. “Geometric deep learning enables 3D kinematic profiling across species and environments.” Nat Methods 18, no. 5 (May 2021): 564–73. https://doi.org/10.1038/s41592-021-01106-6.

Zheng, T., M. Bergin, G. Wang, and D. Carlson. “Local PM2.5 hotspot detector at 300 m resolution: A random forest-convolutional neural network joint model jointly trained on satellite images and meteorology.” Remote Sensing 13, no. 7 (April 1, 2021). https://doi.org/10.3390/rs13071356.

Carson, William, Austin Talbot, and David Carlson. “AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models.” NeurIPS Workshop on Learning Meaningful Representations of Life, 2021.

Zhou, Tianhui, Yitong Li, Yuan Wu, and David Carlson. “Estimating Uncertainty Intervals from Collaborating Networks.” Journal of Machine Learning Research, 2021.

Loring, Zak, Suchit Mehrotra, Jonathan P. Piccini, John Camm, David Carlson, Gregg C. Fonarow, Keith A. A. Fox, Eric D. Peterson, Karen Pieper, and Ajay K. Kakkar. “Machine learning does not improve upon traditional regression in predicting outcomes in atrial fibrillation: an analysis of the ORBIT-AF and GARFIELD-AF registries.” In Europace, 22:1635–44, 2020. https://doi.org/10.1093/europace/euaa172.

Isaev, Dmitry Yu, Dmitry Tchapyjnikov, C Michael Cotten, David Tanaka, Natalia Martinez, Martin Bertran, Guillermo Sapiro, and David Carlson. “Attention-Based Network for Weak Labels in Neonatal Seizure Detection.” Proc Mach Learn Res 126 (August 2020): 479–507.

Isaev, Dmitry Yu, Samantha Major, Michael Murias, Kimberly L. H. Carpenter, David Carlson, Guillermo Sapiro, and Geraldine Dawson. “Relative Average Look Duration and its Association with Neurophysiological Activity in Young Children with Autism Spectrum Disorder.” Sci Rep 10, no. 1 (February 5, 2020): 1912. https://doi.org/10.1038/s41598-020-57902-1.

Lee, JinHyung, Catalin Mitelut, Hooshmand Shokri, Ian Kinsella, Nishchal Dethe, Shenghao Wu, Kevin Li, et al. “YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina.” BioRxiv, 2020. https://doi.org/10.1101/2020.03.18.997924.

Lee, JinHyung, Catalin Mitelut, Hooshmand Shokri, Ian Kinsella, Nishchal Dethe, Shenghao Wu, Kevin Li, et al. “YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina.” BioRxiv, 2020.

Isaev, Dmitry Yu, Samantha Major, Michael Murias, Kimberly L. H. Carpenter, David Carlson, Guillermo Sapiro, and Geraldine Dawson. “Relative Average Look Duration and its Association with Neurophysiological Activity in Young Children with Autism Spectrum Disorder.” Scientific Reports 10 (2020): 1–11.

Zheng, Tongshu, Michael H. Bergin, Shijia Hu, Joshua Miller, and David E. Carlson. “Estimating ground-level PM2. 5 using micro-satellite images by a convolutional neural network and random forest approach.” Atmospheric Environment, 2020, 117451–117451.

Talbot, Austin, David Dunson, Kafui Dzirasa, and David Carlson. “Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity.” ArXiv Preprint ArXiv:2004.05209, 2020.

Block, Carina, Oznur Eroglu, Stephen Mague, Chaichontat Sriworarat, Cameron Blount, Karen Malacon, Kathleen Beben, et al. “Prenatal Environmental Stressors Impair Postnatal Microglia Function and Adult Behavior in Males.” BioRxiv, 2020. https://doi.org/10.1101/2020.10.15.336669.

Cheng, Pengyu, Yitong Li, Xinyuan Zhang, Liqun Cheng, David Carlson, and Lawrence Carin. “Gaussian-Process-Based Dynamic Embedding for Textual Networks.” In AAAI Conference on Artificial Intelligence, 2020.

Mague, Stephen, Austin Talbot, Cameron Blount, Lara Duffney, Kathryn Walder-Christensen, Elise Adamson, Alexandra Bey, et al. “Brain-wide electrical dynamics encode an appetitive socioemotional state.” BioRxiv, 2020. https://doi.org/10.1101/2020.07.01.181347.

Zheng, T., M. H. Bergin, R. Sutaria, S. N. Tripathi, R. Caldow, and D. E. Carlson. “Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi.” Atmospheric Measurement Techniques 12, no. 9 (September 26, 2019): 5161–81. https://doi.org/10.5194/amt-12-5161-2019.

Li, Y., Z. Gan, Y. Shen, J. Liu, Y. Cheng, Y. Wu, L. Carin, D. Carlson, and J. Gao. “Storygan: A sequential conditional gan for story visualization.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2019-June:6322–31, 2019. https://doi.org/10.1109/CVPR.2019.00649.

Zheng, Tongshu, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson. “Supplementary material to "Gaussian Process regression model for dynamically calibrating a wireless low-cost particulate matter sensor network in Delhi",” March 1, 2019. https://doi.org/10.5194/amt-2019-55-supplement.