Preprints

 

“Non-invasive multiphoton imaging of neural structure and activity in Drosophila, 2019 Max Jameson AragonMengran WangJamien Shea, Aaron T. MokHaein Kim, Kawasi M. Lett, Nathan BarkdullChris B. SchafferChris Xu, Nilay Yapici
“Predicting response to motor therapy in chronic stroke patients using Machine Learning”, 2019 Ceren TozluDylan EdwardsAaron BoesDouglas LabarK. Zoe Tsagaris, Joshua Silverstein, Heather Pepper Lane, Mert R. Sabuncu, Charles Liu, Amy Kuceyeski
“Adaptive Compressed Sensing MRI with Unsupervised Learning”, 2019 Cagla D. Bahadir, Adrian V. Dalca, and Mert R. Sabuncu
“Unsupervised Deep Learning for Bayesian Brain MRI Segmentation”, 2019 Adrian Dalca, Evan Yu, Polina Golland, Bruce Fischl, Mert R. Sabuncu, and Juan Eugenio Iglesias
“Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces”, 2019 Adrian V. Dalca, Guha Balakrishnan, John Guttag, and Mert R. Sabuncu
“Learning-based Optimization of the Under-sampling Pattern in MRI”, 2019 Cagla Deniz Bahadir, Adrian V. Dalca, and Mert R. Sabuncu
“Machine learning in resting-state fMRI analysis”, 2018 Meenakshi Khosla, Keith Jamison, Gia H. Ngo, Amy Kuceyeski, Mert R. Sabuncu
“3D Convolutional Neural Networks for Classification of Functional Connectomes”, 2018 Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, and Mert R. Sabuncu
“Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels”, 2018 Zhilu Zhang and Mert R. Sabuncu
“Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration”, 2018 Adrian V. Dalca, Guha Balakrishnan, John Guttag, and Mert R. Sabuncu
“A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome”, 2018 Yingying Zhu and Mert R. Sabuncu