51ÎÛÂþ

Cai, Leon Y., Lee, Ho Hin, Johnson, Graham W., Newlin, Nancy R., Ramadass, Karthik, Kim, Michael E., Archer, Derek B., Hohman, Timothy J., Jefferson, Angela L., Begnoche, J. Patrick, Boyd, Brian D., Taylor, Warren D., Morgan, Victoria L., Englot, Dario J., Nath, Vishwesh, Chotai, Silky, Barquero, Laura, D’Archangel,… Read More

Azher, Zarif L.; Srinivasan, Gokul; Yao, Keluo; Le, Minh-Khang; Lau, Ken S.; Kaur, Harsimran; Kolling, Fred; Vaickus, Louis; Lu, Xiaoying; Levy, Joshua J. “Mapping Three-Dimensional Tumor Heterogeneity through Deep Learning Inference of Spatial… Read More

Gao, Yuxiang; Duddu, Ravindra; Kolouri, Soheil; Gupta, Abhinav; Prabhakar, Pavana. “An inverse design framework for optimizing tensile strength of composite materials based on a CNN surrogate for the phase field fracture model.” Composites Part A: Applied Science and Manufacturing, vol. 192, 2025 51ÎÛÂþ, 108758, https://doi.org/10.1016/j.compositesa.2025 51ÎÛÂþ.108758… Read More

Abbasi, Ali; Nooralinejad, Parsa; Pirsiavash, Hamed; Kolouri, Soheil. “BrainWash: A Poisoning Attack to Forget in Continual Learning.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2024, pp. 24057-24067, https://doi.org/10.1109/CVPR52733.2024.02271.  Continual learning, a field within deep learning,… Read More

Dick, J., Nath, S., Peridis, C., Benjamin, E., Kolouri, S., & Soltoggio, A. (2024). “Statistical Context Detection for Deep Lifelong Reinforcement Learning.” Proceedings of Machine Learning Research, 274, 1013-1031. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85219511357&partnerID=40&md5=44236f24c54c2e13e04ef41cc8a97b90  Context detection involves identifying different tasks within a continuous stream of data. Read More

Lee, Ho Hin; Saunders, Adam M.; Kim, Michael E.; Remedios, Samuel W.; Remedios, Lucas W.; Tang, Yucheng; Yang, Qi; Yu, Xin; Bao, Shunxing; Cho, Chloe; Mawn, Louise A.; Rex, Tonia S.; Schey, Kevin L.; Dewey, Blake E.; Spraggins, Jeffrey M.; Prince, Jerry L.; Huo, Yuankai; Landman, Bennett A. Read More

Ashwin, T.S.; Biswas, Gautam. “Relating Students Cognitive Processes and Learner-Centered Emotions: An Advanced Deep Learning Approach.” ACM International Conference Proceeding Series, 2024, pp. 575-584, https://doi.org/10.1145/3678957.3685751.    Understanding how students regulate their learning, especially in open-ended learning environments, requires looking at… Read More

Saunders, Adam M.; Kim, Michael E.; Gao, Chenyu; Remedios, Lucas W.; Krishnan, Aravind R.; Schilling, Kurt G.; O’Grady, Kristin P.; Smith, Seth A.; Landman, Bennett A. “Comparison and calibration of MP2RAGE quantitative T1 values to multi-TI inversion recovery T1 values.” Magnetic Resonance Imaging, vol. 117,… Read More

Liu, Yihao; Chen, Junyu; Zuo, Lianrui; Carass, Aaron; Prince, Jerry L. “Vector field attention for deformable image registration.” Journal of Medical Imaging, vol. 11, no. 6, 2024, 64001, https://doi.org/10.1117/1.JMI.11.6.064001.  The purpose of this study is to improve the process of… Read More

Cui, C., Yang, H., Wang, Y., Zhao, S., Asad, Z., Coburn, L. A., Wilson, K. T., Landman, B. A., & Huo, Y. (2023). Deep multimodal fusion of image and non-image data in disease diagnosis and prognosis: a review. Progress in Biomedical Engineering, 5(2), 22001. Read More