Search Results for author: Chengsheng Mao

Found 14 papers, 6 papers with code

PANTHER: Pathway Augmented Nonnegative Tensor factorization for HighER-order feature learning

1 code implementation15 Dec 2020 Yuan Luo, Chengsheng Mao

We apply genetically motivated constrained tensor factorization to group pathways in a way that reflects molecular mechanism interactions.

Interpretable Machine Learning

Towards Expressive Graph Representation

1 code implementation12 Oct 2020 Chengsheng Mao, Liang Yao, Yuan Luo

Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning.

Graph Classification Graph Representation Learning

KG-BERT: BERT for Knowledge Graph Completion

3 code implementations7 Sep 2019 Liang Yao, Chengsheng Mao, Yuan Luo

Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness.

Ranked #4 on Link Prediction on FB15k-237 (MR metric)

Knowledge Graph Completion Language Modelling +2

MedGCN: Graph Convolutional Networks for Multiple Medical Tasks

no code implementations31 Mar 2019 Chengsheng Mao, Liang Yao, Yuan Luo

Laboratory testing and medication prescription are two of the most important routines in daily clinical practice.


ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays

no code implementations31 Mar 2019 Chengsheng Mao, Liang Yao, Yuan Luo

However, most of the existing approaches for image representation ignore the relations between images and consider each input image independently.

Object Detection

Local Probabilistic Model for Bayesian Classification: a Generalized Local Classification Model

no code implementations13 Dec 2018 Chengsheng Mao, Lijuan Lu, Bin Hu

In this paper, with the insight that the distribution in a local sample space should be simpler than that in the whole sample space, a local probabilistic model established for a local region is expected much simpler and can relax the fundamental assumptions that may not be true in the whole sample space.

Classification General Classification

Local Distribution in Neighborhood for Classification

no code implementations7 Dec 2018 Chengsheng Mao, Bin Hu, Lei Chen, Philip Moore, Xiaowei Zhang

Additionally, based on the local distribution, we generate a generalized local classification form that can be effectively applied to various datasets through tuning the parameters.

Classification General Classification

Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk

no code implementations27 Sep 2018 Guoqing Chao, Chengsheng Mao, Fei Wang, Yuan Zhao, Yuan Luo

We used the simulation data to verify the effectiveness of this method, and then we applied it to ICU mortality risk prediction and demonstrated its superiority over other conventional supervised NMF methods.

ICU Mortality Time Series

Distribution Networks for Open Set Learning

no code implementations20 Sep 2018 Chengsheng Mao, Liang Yao, Yuan Luo

In this paper, we recognize that novel classes should be different from each other, and propose distribution networks for open set learning that can model different novel classes based on probability distributions.

Classification General Classification +1

Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray Images

1 code implementation20 Sep 2018 Chengsheng Mao, Yiheng Pan, Zexian Zeng, Liang Yao, Yuan Luo

However, most of the previous deep neural network classifiers were based on deterministic architectures which are usually very noise-sensitive and are likely to aggravate the overfitting issue.

General Classification Image Classification

Graph Convolutional Networks for Text Classification

7 code implementations15 Sep 2018 Liang Yao, Chengsheng Mao, Yuan Luo

We build a single text graph for a corpus based on word co-occurrence and document word relations, then learn a Text Graph Convolutional Network (Text GCN) for the corpus.

Classification General Classification +2

Developing a Portable Natural Language Processing Based Phenotyping System

1 code implementation17 Jul 2018 Himanshu Sharma, Chengsheng Mao, Yizhen Zhang, Haleh Vatani, Liang Yao, Yizhen Zhong, Luke Rasmussen, Guoqian Jiang, Jyotishman Pathak, Yuan Luo

Our system facilitates portable phenotyping of obesity and its 15 comorbidities based on the unstructured patient discharge summaries, while achieving a performance that often ranked among the top 10 of the challenge participants.

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