Publications

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.

Zheng, T., M. H. Bergin, K. K. Johnson, S. N. Tripathi, S. Shirodkar, M. S. Landis, R. Sutaria, and D. E. Carlson. “Field evaluation of low-cost particulate matter sensors in high-and low-concentration environments.” Atmospheric Measurement Techniques 11, no. 8 (August 22, 2018): 4823–46. https://doi.org/10.5194/amt-11-4823-2018.

Goldstein, Benjamin A., David Carlson, and Nrupen A. Bhavsar. “Subject Matter Knowledge in the Age of Big Data and Machine Learning.” JAMA Netw Open 1, no. 4 (August 3, 2018): e181568. https://doi.org/10.1001/jamanetworkopen.2018.1568.

Zheng, Tongshu, Michael H. Bergin, Karoline K. Johnson, Sachchida N. Tripathi, Shilpa Shirodkar, Matthew S. Landis, Ronak Sutaria, and David E. Carlson. “Supplementary material to "Field evaluation of low-cost particulate matter sensors in high and low concentration environments",” April 23, 2018. https://doi.org/10.5194/amt-2018-111-supplement.

Hultman, Rainbo, Kyle Ulrich, Benjamin D. Sachs, Cameron Blount, David E. Carlson, Nkemdilim Ndubuizu, Rosemary C. Bagot, et al. “Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability.” Cell 173, no. 1 (March 22, 2018): 166-180.e14. https://doi.org/10.1016/j.cell.2018.02.012.

Vu, Mai-Anh T., Tülay Adalı, Demba Ba, György Buzsáki, David Carlson, Katherine Heller, Conor Liston, et al. “A Shared Vision for Machine Learning in Neuroscience.” J Neurosci 38, no. 7 (February 14, 2018): 1601–7. https://doi.org/10.1523/JNEUROSCI.0508-17.2018.

Zheng, Tongshu, Michael H. Bergin, Karoline K. Johnson, Sachchida N. Tripathi, Shilpa Shirodkar, Matthew S. Landis, Ronak Sutaria, and David E. Carlson. “Field evaluation of low-cost particulate matter sensors in high and low concentration environments.” Atmospheric Measurement Techniques, 2018.

Li, Yitong, Martin Renqiang Min, Dinghan Shen, David Carlson, and Lawrence Carin. “Video Generation From Text.” In AAAI Conference on Artificial Intelligence, 2018.

Liang, Kevin J., Geert Heilmann, Christopher Gregory, Souleymane O. Diallo, David Carlson, Gregory P. Spell, John B. Sigman, Kris Roe, and Lawrence Carin. “Automatic threat recognition of prohibited items at aviation checkpoint with x-ray imaging: a deep learning approach.” In Anomaly Detection and Imaging with X-Rays (ADIX) III, 10632:1063203–1063203, 2018.

Li, Yitong, David E. Carlson, and others. “Extracting relationships by multi-domain matching.” In Advances in Neural Information Processing Systems, 6798–6809, 2018.

Hultman, Rainbo, Kyle Ulrich, Benjamin D. Sachs, Cameron Blount, David E. Carlson, Nkemdilim Ndubuizu, Rosemary C. Bagot, et al. “A convergent depression vulnerability pathway encoded by emergent spatiotemporal dynamics.” Cold Spring Harbor Laboratory, June 23, 2017. https://doi.org/10.1101/154708.

Lee, JinHyung, David Carlson, Hooshmand Shokri, Weichi Yao, Georges Goetz, Espen Hagen, Eleanor Batty, E. J. Chichilnisky, Gaute Einevoll, and Liam Paninski. “YASS: Yet Another Spike Sorter.” Cold Spring Harbor Laboratory, June 19, 2017. https://doi.org/10.1101/151928.

Carlson, David, Lisa K. David, Neil M. Gallagher, Mai-Anh T. Vu, Matthew Shirley, Rainbo Hultman, Joyce Wang, et al. “Dynamically timed stimulation of corticolimbic circuitry activates a stress-compensatory pathway.” Biological Psychiatry 82 (2017): 904–13.

Li, Y., M. Murias, S. Major, G. Dawson, K. Dzirasa, L. Carin, and D. E. Carlson. “Targeting EEG/LFP synchrony with neural nets.” In Advances in Neural Information Processing Systems, 2017-December:4621–31, 2017.

Gallagher, N. M., K. Ulrich, A. Talbot, K. Dzirasa, L. Carin, and D. E. Carlson. “Cross-spectral factor analysis.” In Advances in Neural Information Processing Systems, 2017-December:6843–53, 2017.

Li, Yitong, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, and David E. Carlson. “Targeting EEG/LFP Synchrony with Neural Nets.” Advances in Neural Information Processing Systems, 2017.

Gallagher, Neil M., Kyle Ulrich, Austin Talbot, Kafui Dzirasa, Lawrence Carin, and David E. Carlson. “Cross-Spectral Factor Analysis.” Advances in Neural Information Processing Systems, 2017.

Hultman, Rainbo, Kyle Ulrich, Benjamin Sachs, Cameron Blount, David Carlson, Nkemdilim Ndubuizu, Rosemary Bagot, et al. “A convergent depression vulnerability pathway encoded by emergent spatiotemporal dynamics.” BioRxiv, 2017, 154708–154708.

Pakman, Ari, Dar Gilboa, David Carlson, and Liam Paninski. “Stochastic Bouncy Particle Sampler.” In International Conference on Machine Learning, 2017.

Lee, JinHyung, David Carlson, Hooshmand Shokri, Weichi Yao, Georges Goetz, Espen Hagen, Eleanor Batty, E. J. Chichilnisky, Gaute Einevoll, and Liam Paninski. “YASS: Yet Another Spike Sorter.” Advances in Neural Information Processing Systems, 2017.

Hultman, Rainbo, Stephen D. Mague, Qiang Li, Brittany M. Katz, Nadine Michel, Lizhen Lin, Joyce Wang, et al. “Dysregulation of Prefrontal Cortex-Mediated Slow-Evolving Limbic Dynamics Drives Stress-Induced Emotional Pathology.” Neuron 91, no. 2 (July 20, 2016): 439–52. https://doi.org/10.1016/j.neuron.2016.05.038.

Chen, Changyou, David Carlson, Zhe Gan, Chunyuan Li, and Lawrence Carin. “Bridging the gap between stochastic gradient MCMC and stochastic optimization.” In Artificial Intelligence and Statistics, 1051–60, 2016.

Li, Chunyuan, Changyou Chen, David Carlson, and Lawrence Carin. “Preconditioned stochastic gradient Langevin dynamics for deep neural networks.” In AAAI Conference on Artificial Intelligence, 2016.

Carlson, David, Ya-Ping Hsieh, Edo Collins, Lawrence Carin, and Volkan Cevher. “Stochastic Spectral Descent for Discrete Graphical Models,” 2016.

Merel, Josh, David Carlson, Liam Paninski, and John P. Cunningham. “Neuroprosthetic decoder training as imitation learning.” PLoS Computational Biology 12 (2016).