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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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This is a re-blog from my labmates NICHOLAS J. MATIASZ. It aims to help people get familiar with Git and GitHub workflow. Read more
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This article serves as a proposal that people can use for fast prototyping machine learning models in Tensorflow. You can find the code here. If you find it useful, don’t forget to star the repo and let more people to know. Read more
Internship, UCLA-CSST, 2013
The Cross-disciplinary Scholars in Science and Technology (CSST) program seeks to strengthen international collaboration by inviting highly accomplished students to study and engage in research at UCLA. The students are supported by institutional agreements with universities abroad and by scholarships from their home institutions. Read more
Internship, IQVIA, 2018
Inspired by the healthcare industry, IQVIA commits to providing solutions that enable life sciences companies to innovate with confidence, maximize their opportunities and ultimately drive human health outcomes forward. Read more
Internship, Facebook, 2019
I got the opportunity to work as a machine learning intern at Facebook in 2019 summer. During the 3-month internship, I worked on deep learning models for social search. Specifically, I combined the recent advancement of deep learning and information retrieval to incorporate raw text features into the search ranking system. Our experiments showed promise preliminary results by using raw text features in large-scale social search. Read more
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Talk “Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images” was given on GRS: Advanced Health Informatics, Hong Kong, China. Read more
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Started three months machine learning research internship at IQVIA. Read more
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Our paper “A Basic Phase Diagram of Neuronal Dynamics” has been accepted by Neural Computation. Read more
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Our paper “Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images” has been accepted by IEEE Trans on Medical Imaging. Read more
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Our paper “Semi-supervised Rare Disease Detection Using Generative Adversarial Network” has been accepted by NIPS ML4H 2018 workshop. In addition, I am awarded a travel grant. Read more
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We will present two of our recent work in CVPR workshops this year: “Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach” and “An attention-based multi-resolution model for prostate whole slide imageclassification and localization”. Check them out! Read more
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Our paper “A Social Search Model for Large Scale Social Networks” is now online. Check it out! Read more
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Our paper “Semi-supervised Learning using Adversarial Training with Good and Bad Samples” has been accepted by Machine Vision and Application. Check it out! Read more
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I have successfully defended my PhD dissertation “Improving Data Efficiency on Histopathology Image Analysis Using Deep Learning.” Read more
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We present our work “Gleason grading of biopsies using an attention-based multi-resolution model ensembled with LGBM and XGBoost” in the PANDA challenge workshop of MICCAI 2020. Read more
Published in PIERS Proceedings, 2013
In this work, the graphene is employed to form artificial magnetic conductor (AMC)… Read more
Recommended citation: Wang XC, Li WY, Zhao WS, Hu J, Xu YY, Huang QS. (2013). "Comparative Study on Graphene–Based Artificial Magnetic Conductor (AMC)." PIERS Proceedings, Sweden. Aug 12:496-9.
Published in Nano Letters, 2016
Magnetic skyrmions, which are topologically protected spin textures, are promising candidates for ultralowenergy… Read more
Recommended citation: Guoqiang Yu, Pramey Upadhyaya, Xiang Li, Wenyuan Li, Se Kwon Kim, Yabin Fan, Kin L Wong, Yaroslav Tserkovnyak, Pedram Khalili Amiri, Kang L Wang (2016). "Room-temperature creation and spin–orbit torque manipulation of skyrmions in thin films with engineered asymmetry. " Nano letters. 16(3), 1981-1988.
Published in Optics Express, 2016
In this paper, a nano-pillar array integrated near quantum dots (QDs), which serves as a Purcell cavity as well as a column antenna, is studied… Read more
Recommended citation: Jinxi Huang, Hao Hu, Zhewei Wang, Wenyuan Li, Ji Cang, Jianqi Shen, Hui Ye. (2016). "Analysis of light-emission enhancement of low-efficiency quantum dots by plasmonic nano-particle." Optics Express. 24(8), 8555-8573.
Published in Neural Computation, 2018
The extreme complexity of the brain has attracted the attention of neuroscientists and other researchers for a long time… Read more
Recommended citation: Wenyuan Li , Igor V. Ovchinnikov , Honglin Chen , Zhe Wang , Albert Lee , Houchul Lee , Carlos Cepeda , Robert N. Schwartz , Karlheinz Meier and Kang L. Wang(2018). "A Basic Phase Diagram of Neuronal Dynamics" Neural Computation. 30(9), 2418-2438
Published in IEEE Trans on Medical Imaging, 2018
Prostate cancer is the most common and second most deadly form of cancer in men in the United States… Read more
Recommended citation: Wenyuan Li, Jiayun Li, Karthik V. Sarma, King Chung Ho, Shiwen Shen, Beatrice S. Knudsen, Arkadiusz Gertych, and Corey W. Arnold (2018). "Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images." IEEE transactions on medical imaging.
Published in NIPS ML4H 2018 workshop, 2018
Rare diseases affect a relatively small number of people, which limits investment in research for treatments… Read more
Recommended citation: Wenyuan Li, Yunlong Wang, Yong Cai, Corey Arnold, Emily Zhao, and Yilian Yuan (2018). "Semi-supervised Rare Disease Detection Using Generative Adversarial Network." NIPS Machine Learning for Healthcare Workshop.
Published in CVPR LID 2019 workshop, 2019
Recently, semi-supervised learning methods based on generative adversarial networks (GANs) have received much attention. Among them, two distinct approaches have achieved… Read more
Recommended citation: Wenyuan Li, Zichen Wang, Jiayun Li, Jennifer Polson, William Speier and Corey Arnold (2019). " Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach." CVPR LID Workshop.
Published in Arxiv, 2020
With the rise of social networks, information on the internet is no longer solely organized by web pages. Rather, … Read more
Recommended citation: Yunzhong He, Wenyuan Li, Liang-Wei Chen, Gabriel Forgues, Xunlong Gui, Sui Liang, and Bo Hou (2020). " A Social Search Model for Large Scale Social Networks. " arXiv preprint arXiv:2005.04356.
Published in Machine Vision and Application (Springer), 2020
In this work, we investigate semi-supervised learning (SSL) for image classification using adversarial training. Previous results have illustrated that generative adversarial networks (GANs)… Read more
Recommended citation: Wenyuan Li, Zichen Wang, Yuguang Yue, Jiayun Li, William Speier, Mingyuan Zhou and Corey Arnold (2020). " Semi-supervised Learning using Adversarial Training with Good and Bad Samples ." Machine Vision and Application 31.6, 1-11..
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High school student course, New Oriental Education & Technology Group, 2014
As the largest provider of private educational services in China, New Oriental offers education for a lifetime, teaching skills that give students a crucial competitive advantage in the workplace and help improve their quality of life. Read more
Senior high school student AI course, Embark China, 2017
Embark China provides unique extracurricular activities with an international focus to talented Chinese high school students. In today’s rapidly growing Chinese education industry, Embark has established itself as the leader in experiential learning by emphasizing the skills that modern, international university students need. Embark has partnered with U.S. universities and academic organizations across a variety of disciplines to offer academic environments and resources that reach the cutting-edge technologies. Read more
General education course, University of California, Los Angeles, Life Science Department, 2017
This class opened by life science department was a General Education (GE) course for UCLA undergraduate student. It enforced me to become a faster learner in a short period of time since the contents of the class were not familiar to me. Moreover, I improved my skill to explain certain concepts to different people from different background, which I believed is important for future career. Read more