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Review of unsupervised pretraining strategies for molecules representation
In recent years, the computer-assisted techniques make a great progress in the field of drug
discovery. And, yet, the problem of limited labeled data problem is still challenging and also …
discovery. And, yet, the problem of limited labeled data problem is still challenging and also …
Graph neural networks are more powerful than we think
Graph Neural Networks (GNNs) are powerful architectures that have demonstrated
remarkable performance in various node-level and graph-level tasks. Despite this success …
remarkable performance in various node-level and graph-level tasks. Despite this success …
[HTML][HTML] EMBER—Embedding multiple molecular fingerprints for virtual screening
In recent years, the debate in the field of applications of Deep Learning to Virtual Screening
has focused on the use of neural embeddings with respect to classical descriptors in order to …
has focused on the use of neural embeddings with respect to classical descriptors in order to …
[HTML][HTML] Boosting heterogeneous catalyst discovery by structurally constrained deep learning models
The discovery of new catalysts is one of the significant topics of computational chemistry as it
has the potential to accelerate the adoption of renewable energy sources. Recently …
has the potential to accelerate the adoption of renewable energy sources. Recently …
[PDF][PDF] Development of universal data representations with application in chemistry.
M Wiercioch - 2023 - ruj.uj.edu.pl
Opracowanie uniwersalnych metod reprezentacji danych do poprawy jakosci metod uczenia
maszynowego z przykładowym zastosowaniem w chemii W ostatnich latach modele bazuj …
maszynowego z przykładowym zastosowaniem w chemii W ostatnich latach modele bazuj …
[کتاب][B] 詳解 マテリアルズインフォマティクス: 有機・無機化学のための深層学習
船津公人, 井上貴央, 西川大貴 - 2021 - books.google.com
化学の研究開発ではマテリアルズインフォマティクス (機械学習・深層学習を用いた新素材探索や
新材料設計) の技術が導入され始めています. 一方で, 有機化学・無機化学のどの領域かによって …
新材料設計) の技術が導入され始めています. 一方で, 有機化学・無機化学のどの領域かによって …