Publications

Found 77 results
Type [ Year(Asc)]
2021
T Dunn, JD Marshall, KS Severson, DE Aldarondo, DGC Hildebrand, SN Chettih, WL Wang, AJ Gellis, DE Carlson, D Aronov et al. "Geometric deep learning enables 3D kinematic profiling across species and environments." Nature Methods (In press) (2021).
TW Dunn, JD Marshall, KS Severson, DE Aldarondo, DGC Hildebrand, SN Chettih, WL Wang, AJ Gellis, DE Carlson, D Aronov et al. "Geometric deep learning enables 3D kinematic profiling across species and environments." Nat Methods 18, no. 5 (2021): 564-573.
T Zheng, 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 (2021): 1356.
2020
DY Isaev, D Tchapyjnikov, CM Cotten, D Tanaka, N Martinez, M Bertran, G Sapiro, and D Carlson. "Attention-Based Network for Weak Labels in Neonatal Seizure Detection." Proc Mach Learn Res 126 (2020): 479-507.
P Cheng, Y Li, X Zhang, L Chen, D Carlson, and L Carin. "Dynamic embedding on textual networks via a Gaussian process." Aaai 2020 34th Aaai Conference on Artificial Intelligence (2020): 7562-7569.
T Zheng, MH Bergin, S Hu, J Miller, and DE Carlson. "Estimating ground-level PM2. 5 using micro-satellite images by a convolutional neural network and random forest approach." Atmospheric Environment (2020): 117451.
T Zheng, MH Bergin, S Hu, J Miller, and DE Carlson. "Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach." Atmospheric Environment 230 (2020): 117451.
T Zhou, Y Li, Y Wu, and D Carlson. "Estimating Uncertainty Intervals from Collaborating Networks." Arxiv Preprint Arxiv:2002.05212 (2020).
P Cheng, Y Li, X Zhang, L Cheng, D Carlson, and L Carin. "Gaussian-Process-Based Dynamic Embedding for Textual Networks." In Aaai Conference on Artificial Intelligence. 2020.
Z Loring, S Mehrotra, JP Piccini, J Camm, D Carlson, GC Fonarow, KAA Fox, ED Peterson, K Pieper, and AK 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, 1635-1644. Vol. 22. 2020.
DY Isaev, S Major, M Murias, KLH Carpenter, D Carlson, G Sapiro, and G Dawson. "Relative Average Look Duration and its Association with Neurophysiological Activity in Young Children with Autism Spectrum Disorder." Scientific Reports 10 (2020): 1-11.
A Talbot, D Dunson, K Dzirasa, and D Carlson. "Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity." Arxiv Preprint Arxiv:2004.05209 (2020).
A Talbot, DB Dunson, K Dzirasa, and DE Carlson. "Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity." Corr abs/2004.05209 (2020).
Y Li, M Murias, S Major, G Dawson, and DE Carlson. "On target shift in adversarial domain adaptation." In Aistats 2019 22nd International Conference on Artificial Intelligence and Statistics. 2020.
J Lee, C Mitelut, H Shokri, I Kinsella, N Dethe, S Wu, K Li, EB Reyes, D Turcu, E Batty et al. "YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina." Biorxiv (2020).
2019
D Carlson, and L Carin. "Continuing progress of spike sorting in the era of big data." Current Opinion in Neurobiology 55 (2019): 90-96.
D Carlson, and L Carin. "Continuing progress of spike sorting in the era of big data." Current Opinion in Neurobiology 55 (2019): 90-96.
T Zheng, MH Bergin, R Sutaria, SN Tripathi, R Caldow, and DE 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 (2019): 5161-5181.
Z Loring, S Mehrotra, JP Piccini, J Camm, D Carlson, GC Fonarow, KA Fox, ED Peterson, KS Pieper, and AK 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 Circulation. Vol. 140. 2019.
C Norris, L Fang, KK Barkjohn, D Carlson, Y Zhang, J Mo, Z Li, J Zhang, X Cui, JJ Schauer 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): 256-268.
C Norris, L Fang, KK Barkjohn, D Carlson, Y Zhang, J Mo, Z Li, J Zhang, X Cui, JJ Schauer 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): 256-268.
Y Li, 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, 6322-6331. Vol. 2019-June. 2019.
Y Li, M Murias, S Major, G Dawson, and DE Carlson. "On Target Shift in Adversarial Domain Adaptation." In International Conference on Artificial Intelligence and Statistics, 616-625. 2019.
2018
KJ Liang, G Heilmann, C Gregory, SO Diallo, D Carlson, GP Spell, JB Sigman, K Roe, and L 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, 1063203. Vol. 10632. 2018.
R Hultman, K Ulrich, BD Sachs, C Blount, DE Carlson, N Ndubuizu, RC Bagot, EM Parise, M-AT Vu, NM Gallagher et al. "Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability." Cell 173, no. 1 (2018): 166-180.e14.

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