REST: Drug-Drug Interaction Prediction via Reinforced Student-Teacher Curriculum Learning-Reference-Cited by-同舟云学术

REST: Drug-Drug Interaction Prediction via Reinforced Student-Teacher Curriculum Learning

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Li Xinhang¹^ORCID,Qiu Zhaopeng²^ORCID,Zhao Xiangyu³^ORCID,Zhang Yong¹^ORCID,Xing Chunxiao¹^ORCID,Wu Xian⁴^ORCID

Affiliation:

1. Tsinghua University, Beijing, China

2. BOSS Zhipin, Beijing, China

3. City University of Hong Kong, Hong Kong, Hong Kong

4. Tencent Jarvis Lab, Beijing, China

Funder

SIRG - CityU Strategic Interdisciplinary Research Grant

National Natural Science Foundation of China

Diversified Investment Foundation of Tianjin

CCF-Ant Research Fund

CityU - HKIDS Early Career Research Grant

CCF-Tencent Open Fund

Tencent Rhino-Bird Focused Research Fund

APRC - CityU New Research Initiatives

Hong Kong ITC Innovation and Technology Fund Midstream Research Programme for Universities Project

Ant Group Research Fund

Huawei Innovation Research Program

Tencent Rhino-Bird Research Elite Training Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615033

Reference53 articles.

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4. Yin Cui , Menglin Jia , Tsung-Yi Lin , Yang Song , and Serge J . Belongie . 2019 . Class-Balanced Loss Based on Effective Number of Samples. In CVPR. 9268--9277. Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, and Serge J. Belongie. 2019. Class-Balanced Loss Based on Effective Number of Samples. In CVPR. 9268--9277.

5. A multimodal deep learning framework for predicting drug–drug interaction events