3 citations · 5 across the 2 of their papers we have counts for
4 papers
Multiple-shooting adjoint method for whole-brain dynamic causal modeling
Juntang Zhuang, Nicha Dvornek, Sekhar Tatikonda +3
Dynamic causal modeling (DCM) is a Bayesian framework to infer directed connections between compartments, and has been used to describe the interactions between underlying neural p…
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
Juntang Zhuang, Tommy Tang, Yifan Ding +4
Most popular optimizers for deep learning can be broadly categorized as adaptive methods (e.g. Adam) and accelerated schemes (e.g. stochastic gradient descent (SGD) with momentum).…
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li +3
Neural ordinary differential equations (NODEs) have recently attracted increasing attention; however, their empirical performance on benchmark tasks (e.g. image classification) are…
Evaluation of CT Image Synthesis Methods:From Atlas-based Registration to Deep Learning
Andreas D. Lauritzen, Xenophon Papademetris, Sergei Turovets +1
Computed tomography (CT) is a widely used imaging modality for medical diagnosis and treatment. In electroencephalography (EEG), CT imaging is necessary for co-registering with mag…