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Yukun Ding
Researcher at University of Notre Dame
Publications - 25
Citations - 521
Yukun Ding is an academic researcher from University of Notre Dame. The author has contributed to research in topics: Artificial neural network & Segmentation. The author has an hindex of 8, co-authored 25 publications receiving 324 citations. Previous affiliations of Yukun Ding include Beijing University of Posts and Telecommunications.
Papers
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Journal ArticleDOI
Scaling for edge inference of deep neural networks
TL;DR: There are increasing gaps between the computational complexity and energy efficiency required for the continued scaling of deep neural networks and the hardware capacity actually available with current CMOS technology scaling, in situations where edge inference is required.
Proceedings ArticleDOI
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off
TL;DR: In this paper, the authors focus on two main use cases of uncertainty estimation, i.e., selective prediction and confidence calibration, and apply these new metrics to explore the trade-off between model complexity and uncertainty estimation quality.
Proceedings Article
On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks
TL;DR: This paper proves the universal approximability of quantized ReLU networks on a wide class of functions and provides upper bounds on the number of weights and the memory size for a given approximation error bound and the bit-width of weights for function-independent and function-dependent structures.
Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation
TL;DR: A novel method is presented that considers such uncertainty in the training process to maximize the accuracy on the confident subset rather than the Accuracy on the whole dataset.
Journal ArticleDOI
Hardware design and the competency awareness of a neural network
Yukun Ding,Weiwen Jiang,Qiuwen Lou,Jinglan Liu,Jinjun Xiong,Xiaobo Sharon Hu,Xiaowei Xu,Yiyu Shi +7 more
TL;DR: The relationship between hardware platforms and the competency awareness of a neural network is examined, highlighting how hardware developments can impact uncertainty estimation quality, and exploring the innovations required in order to build competency-aware neural networks in resource constrained hardware platforms.