Search Results for author: Kuo Yang

Found 11 papers, 4 papers with code

A optimization framework for herbal prescription planning based on deep reinforcement learning

no code implementations25 Apr 2023 Kuo Yang, Zecong Yu, Xin Su, Xiong He, Ning Wang, Qiguang Zheng, Feidie Yu, Zhuang Liu, Tiancai Wen, Xuezhong Zhou

We constructed a high-quality benchmark dataset for sequential diagnosis and treatment of diabetes and evaluated PrescDRL against this benchmark.

reinforcement-learning Sequential Diagnosis

Knowledge Graph Completion based on Tensor Decomposition for Disease Gene Prediction

1 code implementation18 Feb 2023 Xinyan Wang, Ting Jia, Chongyu Wang, Kuan Xu, Zixin Shu, Jian Yu, Kuo Yang, Xuezhong Zhou

In this paper, we construct a biological knowledge graph centered on diseases and genes, and develop an end-to-end Knowledge graph completion model for Disease Gene Prediction using interactional tensor decomposition (called KDGene).

Knowledge Graph Completion Tensor Decomposition

A Pre-training Framework for Knowledge Graph Completion

no code implementations6 Feb 2023 Kuan Xu, Kuo Yang, Hanyang Dong, Xinyan Wang, Jian Yu, Xuezhong Zhou

Knowledge graph completion (KGC) is one of the effective methods to identify new facts in knowledge graph.

Knowledge Graph Completion

CLAD: A realistic Continual Learning benchmark for Autonomous Driving

1 code implementation7 Oct 2022 Eli Verwimp, Kuo Yang, Sarah Parisot, Hong Lanqing, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars

In this paper we describe the design and the ideas motivating a new Continual Learning benchmark for Autonomous Driving (CLAD), that focuses on the problems of object classification and object detection.

Autonomous Driving Continual Learning +2

Memory Replay with Data Compression for Continual Learning

1 code implementation ICLR 2022 Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu

In this work, we propose memory replay with data compression (MRDC) to reduce the storage cost of old training samples and thus increase their amount that can be stored in the memory buffer.

Autonomous Driving class-incremental learning +6

TCMPR: TCM Prescription recommendation based on subnetwork term mapping and deep learning

1 code implementation 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2021 Xin Dong, Yi Zheng, Zixin Shu, Kai Chang, Dengying Yan, Jianan Xia, Qiang Zhu, Kunyu Zhong, Xinyan Wang, Kuo Yang, Xuezhong Zhou

In addition, the comprehensive experiments of TCMPR with different hyper parameters (i. e., feature embedding, feature dimension and feature fusion) that demonstrates that our method has high performance on TCM prescription recommendation and potentially promote clinical diagnosis and treatment of TCM precision medicine.

Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images

no code implementations25 Feb 2021 Kuo Yang, Emad A. Mohammed, Behrouz H. Far

We use the similarity graph as a regularizer in the loss function of a CNN model to minimize the distance between the input images and their k-nearest neighbours in the similarity graph while minimizing the categorical cross-entropy loss between the training image predictions and the actual image class labels.

Clustering Dimensionality Reduction

Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation

no code implementations5 Jan 2021 Qijun Luo, Zhili Liu, Lanqing Hong, Chongxuan Li, Kuo Yang, Liyuan Wang, Fengwei Zhou, Guilin Li, Zhenguo Li, Jun Zhu

Semi-supervised domain adaptation (SSDA), which aims to learn models in a partially labeled target domain with the assistance of the fully labeled source domain, attracts increasing attention in recent years.

Domain Adaptation Semi-supervised Domain Adaptation

A Review of Artificial Intelligence Technologies for Early Prediction of Alzheimer's Disease

no code implementations22 Dec 2020 Kuo Yang, Emad A. Mohammed

The reliable and effective evaluation of early dementia has become essential research with medical imaging technologies and computer-aided algorithms.

Ensemble Learning Image Classification +3

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