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Double-Uncertainty Weighted Method for Semi-supervised Learning

Oct 19, 2020
Yixin Wang, Yao Zhang, Jiang Tian, Cheng Zhong, Zhongchao Shi, Yang Zhang, Zhiqiang He

* accepted by MICCAI 2020 

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Modality-Pairing Learning for Brain Tumor Segmentation

Oct 19, 2020
Yixin Wang, Yao Zhang, Feng Hou, Yang Liu, Jiang Tian, Cheng Zhong, Yang Zhang, Zhiqiang He

* 10 pages 

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Point process models for sequence detection in high-dimensional neural spike trains

Oct 10, 2020
Alex H. Williams, Anthony Degleris, Yixin Wang, Scott W. Linderman

* 24 pages, 5 figures 

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Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation

Jun 23, 2020
Yixin Wang, Yao Zhang, Yang Liu, Jiang Tian, Cheng Zhong, Zhongchao Shi, Yang Zhang, Zhiqiang He

* 9 pages 

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Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation

Apr 27, 2020
Jun Ma, Yixin Wang, Xingle An, Cheng Ge, Ziqi Yu, Jianan Chen, Qiongjie Zhu, Guoqiang Dong, Jian He, Zhiqiang He, Ziwei Nie, Xiaoping Yang

* 7 pages 

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Towards Clarifying the Theory of the Deconfounder

Mar 10, 2020
Yixin Wang, David M. Blei


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The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge

Dec 02, 2019
Nicholas Heller, Fabian Isensee, Klaus H. Maier-Hein, Xiaoshuai Hou, Chunmei Xie, Fengyi Li, Yang Nan, Guangrui Mu, Zhiyong Lin, Miofei Han, Guang Yao, Yaozong Gao, Yao Zhang, Yixin Wang, Feng Hou, Jiawei Yang, Guangwei Xiong, Jiang Tian, Cheng Zhong, Jun Ma, Jack Rickman, Joshua Dean, Bethany Stai, Resha Tejpaul, Makinna Oestreich, Paul Blake, Heather Kaluzniak, Shaneabbas Raza, Joel Rosenberg, Keenan Moore, Edward Walczak, Zachary Rengel, Zach Edgerton, Ranveer Vasdev, Matthew Peterson, Sean McSweeney, Sarah Peterson, Arveen Kalapara, Niranjan Sathianathen, Christopher Weight, Nikolaos Papanikolopoulos

* 18 pages, 7 figures 

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The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019)

Oct 17, 2019
Yixin Wang, David M. Blei


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Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes

Oct 05, 2019
Yao Zhang, Yixin Wang, Feng Hou, Jiawei Yang, Guangwei Xiong, Jiang Tian, Cheng Zhong


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Multiple Causes: A Causal Graphical View

May 30, 2019
Yixin Wang, David M. Blei

* 23 pages 

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Equal Opportunity and Affirmative Action via Counterfactual Predictions

May 29, 2019
Yixin Wang, Dhanya Sridhar, David M. Blei

* 18 pages 

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Variational Bayes under Model Misspecification

May 26, 2019
Yixin Wang, David M. Blei

* 27 pages 

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The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs)

Apr 03, 2019
Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak


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Using Embeddings to Correct for Unobserved Confounding

Feb 11, 2019
Victor Veitch, Yixin Wang, David M. Blei


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The Deconfounded Recommender: A Causal Inference Approach to Recommendation

Aug 20, 2018
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei

* 14 pages, 3 figures 

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Robust Probabilistic Modeling with Bayesian Data Reweighting

Jun 19, 2018
Yixin Wang, Alp Kucukelbir, David M. Blei

* In ICML 2017. Updated related work 

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The Blessings of Multiple Causes

Jun 19, 2018
Yixin Wang, David M. Blei

* 59 pages 

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Black Box FDR

Jun 08, 2018
Wesley Tansey, Yixin Wang, David M. Blei, Raul Rabadan

* To appear at ICML'18; code available at https://github.com/tansey/bb-fdr 

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Frequentist Consistency of Variational Bayes

May 24, 2018
Yixin Wang, David M. Blei

* 58 pages 

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