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Cross-Adversarial Learning for Molecular Generation in Drug Design

Banghua Wu, Linjie Li, Yue Cui, Kai Zheng
2022 Frontiers in Pharmacology  
Considering these challenges, we propose a cross-adversarial learning method for molecular generation, CRAG for short, which integrates both the facticity of VAE-based methods and the diversity of GAN-based  ...  Extensive experiments on two widely used benchmarks have demonstrated the effectiveness of our proposed method on a wide spectrum of metrics.  ...  , Rhodes, Greece, October 4-7, 2018 (Springer), 11139, 412–422.  ... 
doi:10.3389/fphar.2021.827606 pmid:35126153 pmcid:PMC8815768 fatcat:ukkolh2g7zdhxhvk2dtnweyv2u

A Survey of Deep Active Learning [article]

Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Brij B. Gupta, Xiaojiang Chen, Xin Wang
2021 arXiv   pre-print
This is mainly because before the rise of DL, traditional machine learning requires relatively few labeled samples. Therefore, early AL is difficult to reflect the value it deserves.  ...  Deep learning (DL) is greedy for data and requires a large amount of data supply to optimize massive parameters, so that the model learns how to extract high-quality features.  ...  In Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II (Lecture  ... 
arXiv:2009.00236v2 fatcat:zuk2doushzhlfaufcyhoktxj7e