A Comparative Study of Metric-based Meta-Learning Methods for Improving Few-Shot Learning in Drug Discovery with Limited Data-Reference-Cited by-同舟云学术

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A Comparative Study of Metric-based Meta-Learning Methods for Improving Few-Shot Learning in Drug Discovery with Limited Data

Published:2024-04-17 Issue: Volume:43 Page:601-606
ISSN:
Container-title:2024 International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS)
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Author:

George Gilda¹,Juliet Sujitha¹

Affiliation:

1. Karunya Institute of Technology and Sciences,Division of Data Science amd Cyber Security,Coimbatore,Tamil Nadu,641114

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10533880/10533882/10533948.pdf?arnumber=10533948

Reference18 articles.

1. Artificial Intelligence in Drug Discovery: Applications and Techniques;Ahmed,2021

2. Highway Bridge Superstructure Engineering

3. Few-shot learning for low-data drug discovery;Sun;IEEE Transactions on Pattern Analysis and Machine Intelligence,2021

4. Learning from few examples: A summary of approaches to few-shot learning;Parnami,2022

5. Optimization as a model for few-shot learning;Ravi

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