Search Results for author: Yukun Ding

Found 12 papers, 2 papers with code

Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

2 code implementations29 Jun 2021 Dewen Zeng, Mingqi Li, Yukun Ding, Xiaowei Xu, Qiu Xie, Ruixue Xu, Hongwen Fei, Meiping Huang, Jian Zhuang, Yiyu Shi

Experiment results on our clinical MCE data set demonstrate that the neural network trained with the proposed loss function outperforms those existing ones that try to obtain a unique ground truth from multiple annotations, both quantitatively and qualitatively.

Image Segmentation Segmentation +1

On the Universal Approximability and Complexity Bounds of Deep Learning in Hybrid Quantum-Classical Computing

no code implementations1 Jan 2021 Weiwen Jiang, Yukun Ding, Yiyu Shi

With the continuously increasing number of quantum bits in quantum computers, there are growing interests in exploring applications that can harvest the power of them.

Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising

no code implementations27 Feb 2020 Jinglan Liu, Yukun Ding, JinJun Xiong, Qianjun Jia, Meiping Huang, Jian Zhuang, Bike Xie, Chun-Chen Liu, Yiyu Shi

For example, if the noise is large leading to significant difference between domain $X$ and domain $Y$, can we bridge $X$ and $Y$ with an intermediate domain $Z$ such that both the denoising process between $X$ and $Z$ and that between $Z$ and $Y$ are easier to learn?

Image Denoising Image-to-Image Translation +1

Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation

no code implementations MIDL 2019 Yukun Ding, Jinglan Liu, Xiaowei Xu, Meiping Huang, Jian Zhuang, JinJun Xiong, Yiyu Shi

Existing selective segmentation methods, however, ignore this unique property of selective segmentation and train their DNN models by optimizing accuracy on the entire dataset.

Image Segmentation Medical Image Segmentation +2


no code implementations ICLR 2020 Akash Srivastava, Yamini Bansal, Yukun Ding, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund

In this work, we tackle a slightly more intricate scenario where the observations are generated from a conditional distribution of some known control variate and some latent noise variate.


Real-Time Boiler Control Optimization with Machine Learning

no code implementations7 Mar 2019 Yukun Ding, Yiyu Shi

In coal-fired power plants, it is critical to improve the operational efficiency of boilers for sustainability.

BIG-bench Machine Learning FLUE

Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off

1 code implementation5 Mar 2019 Yukun Ding, Jinglan Liu, JinJun Xiong, Yiyu Shi

Accurately estimating uncertainties in neural network predictions is of great importance in building trusted DNNs-based models, and there is an increasing interest in providing accurate uncertainty estimation on many tasks, such as security cameras and autonomous driving vehicles.

Autonomous Driving

PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence

no code implementations26 Feb 2018 Jinglan Liu, Jiaxin Zhang, Yukun Ding, Xiaowei Xu, Meng Jiang, Yiyu Shi

This work explores the binarization of the deconvolution-based generator in a GAN for memory saving and speedup of image construction.


On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks

no code implementations ICLR 2019 Yukun Ding, Jinglan Liu, JinJun Xiong, Yiyu Shi

To the best of our knowledge, this is the first in-depth study on the complexity bounds of quantized neural networks.


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