2021-02-14
@article{zhuang2020adabelief, title={AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients}, author={Zhuang, Juntang and Tang, Tommy and Ding, Yifan and Tatikonda, Sekhar and Dvornek, Nicha and Papademetris, Xenophon and Duncan, James}, journal={Conference on Neural Information Processing Systems}, year={2020} }
Last released on Feb 10, 2021 PyTorch implementation of reverse Juntang Zhuang · Tommy Tang · Yifan Ding · Sekhar C Tatikonda · Nicha Dvornek · Xenophon Papademetris · James Duncan. Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1864 in Poster Session 7 » Most popular Juntang Zhuang James Duncan Significant progress has been made using fMRI to characterize the brain changes that occur in ASD, a complex neuro-developmental disorder. List of computer science publications by Juntang Zhuang Semantic Scholar profile for Juntang Zhuang, with 28 highly influential citations and 26 scientific research papers. Xiaoxiao LI*, Nicha Dvornek, Xenophon Papademetris, Juntang Zhuang, Lawrence H. Staib, Pamela Ventola, James Duncan 2-Channel Convolutional 3D Deep Neural Network (2CC3D) for fMRI Analysis: ASD Classification and Feature Learning (ISBI 2018, oral presentation) Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Daniel Yang, Pamela Ventola, James Duncan Prediction of pivotal response treatment … 2018-11-27 author = {Yang, Junlin and Dvornek, Nicha C. and Zhang, Fan and Zhuang, Juntang and Chapiro, Julius and Lin, MingDe and Duncan, James S.}, title = {Domain-Agnostic Learning With Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, Juntang Zhuang, Nicha C. Dvornek, Qingyu Zhao, Xiaoxiao Li, Pamela Ventola, James S. Duncan. [Paper] Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection Juntang Zhuang.
See the complete profile on LinkedIn and discover Update for adabelief-tf==0.2.0 (Crucial). In adabelief-tf==0.1.0, we modify adabelief-tf to have the same feature as adabelief-pytorch, inlcuding decoupled weight decay and learning rate rectification. Juntang Zhuang · Tommy Tang · Yifan Ding · Sekhar C Tatikonda · Nicha Dvornek · Xenophon Papademetris · James Duncan Thu Dec 10 09:00 PM -- 11:00 PM (PST) @ Poster Session 6 #1864 Juntang Zhuang James Duncan Significant progress has been made using fMRI to characterize the brain changes that occur in ASD, a complex neuro-developmental disorder. U-Net has been providing state-of-the-art performance in many medical image segmentation problems.
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Juntang Zhuang 1 , Nicha C Dvornek 2 3 , Qingyu Zhao 4 , Xiaoxiao Li 1 , Pamela Ventola 2 , James S Duncan 1 3 Affiliations 1 Biomedical Engineering, Yale University, New Haven, CT, USA.
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all Juntang Zhuang, Nicha Dvornek, Sekhar Tatikonda, Xenophon Papademetris, Pamela Ventola , James S. Duncan , Paper Code Package. Abstract . Dynamic causal modeling (DCM @article{zhuang2020adabelief, title={AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients}, author={Zhuang, Juntang and Tang, Tommy and Tatikonda, Sekhar and and Dvornek, Nicha and Ding, Yifan and Papademetris, Xenophon and Duncan, James}, journal={Conference on Neural Information Processing Systems}, year={2020}} Authors: Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan Download PDF Abstract: Neural ordinary differential equations (Neural ODEs) are a new family of deep-learning models with continuous depth. juntang-zhuang/ShelfNet-lw-cityscapes.
Juntang ZHUANG | Cited by 81 | of Yale University, CT (YU) | Read 32 publications | Contact Juntang ZHUANG
We provide link to the implementation https://github.com/ juntang- zhuang/ [2] Zhuang, Juntang, et al. "Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE." arXiv preprint arXiv:2006.02493 (2020). Add Comment. the quality of generated samples compared to a well-tuned Adam optimizer. Code is available at https://github.com/juntang-zhuang/Adabelief-Optimizer. Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, 23 Oct 2020 Xiaoxiao Li, Yuan Zhou, Siyuan Gao, Nicha Dvornek, Muhan Zhang, Juntang Zhuang, Shi Gu, Dustin Scheinost, Lawrence Staib, Pamela X Li, NC Dvornek, X Papademetris, J Zhuang, LH Staib, P Ventola, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018. Yan Ge, Jun Ma, Li Zhang, Haiping Lu, Unifying Homophily and Heterophily Haiping Lu, Nicha C Dvornek, Juntang Zhuang, Gideon Pinto, Sandip Samal, [Spotlight at NeurIPS 2020] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients.
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Juntang Zhuang, Nicha C. Dvornek, Qingyu Zhao, Xiaoxiao Li, Pamela Ventola, James S. Duncan. [Paper] Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection
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∙ 48 ∙ share Most popular optimizers for deep learning can be broadly categorized as adaptive methods (e.g. Adam) and accelerated schemes (e.g.
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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).
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[1] Zhuang, Juntang, et al. "Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE." arXiv preprint arXiv:2006.02493 (2020). Please cite our paper if you find this repository useful:
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2020-10-15 · Authors: Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar Tatikonda, Nicha Dvornek, Xenophon Papademetris, James S. Duncan Download PDF Abstract: 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).
AdaBelief Optimizer: Adapting Stepsizes by the Belief in… Observed Gradients.