Walder-Christensen, Kathryn, Karim Abdelaal, Hunter Klein, Gwenaëlle E. Thomas, Neil M. Gallagher, Austin Talbot, Elise Adamson, et al. “Electome network factors: Capturing emotional brain networks related to health and disease.” Cell Rep Methods 4, no. 1 (January 22, 2024): 100691.

Calhoun, Zachary D., Frank Willard, Chenhao Ge, Claudia Rodriguez, Mike Bergin, and David Carlson. “Estimating the effects of vegetation and increased albedo on the urban heat island effect with spatial causal inference.” Scientific Reports 14, no. 1 (January 2024): 540.


Grossman, Yael S., Austin Talbot, Neil M. Gallagher, Gwenaëlle E. Thomas, Alexandra J. Fink, Kathryn K. Walder-Christensen, Scott J. Russo, David E. Carlson, and Kafui Dzirasa. “Brain-wide oscillatory network encodes an aggressive internal state.” Cold Spring Harbor Laboratory, December 7, 2022.

Jiang, Z., T. Zheng, M. Bergin, and D. Carlson. “Improving spatial variation of ground-level PM2.5 prediction with contrastive learning from satellite imagery.” Science of Remote Sensing 5 (June 1, 2022).

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.


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.

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.

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).

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.

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.

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.

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.


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.

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.

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.

Li, Yitong, Michael Murias, Samantha Major, Geraldine Dawson, and David E. Carlson. “On Target Shift in Adversarial Domain Adaptation.” In International Conference on Artificial Intelligence and Statistics, 2019.

Carlson, David, and Lawrence Carin. “Continuing progress of spike sorting in the era of big data.” Current Opinion in Neurobiology 55 (2019): 90–96.

Norris, Christina, Lin Fang, Karoline K. Barkjohn, David Carlson, Yinping Zhang, Jinhan Mo, Zhen Li, et al. “Sources of volatile organic compounds in suburban homes in Shanghai, China, and the impact of air filtration on compound concentrations.” Chemosphere 231 (2019): 256–68.

Rudin, Cynthia, and David Carlson. “The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to Be More Effective at Data Analysis.” In Operations Research & Management Science in the Age of Analytics, 44–72. INFORMS, 2019.