Description:
Explore geometric deep learning techniques for drug discovery in this 58-minute webinar presented by Jian Tang from MILA/HEC Montreal. Delve into various types of data, research problems, and graph neural networks used in the field. Learn about infograph, mutual information, and graph AF, along with experimental results in gold-directed molecule generation, constraint optimization, and retrosynthetic prediction. Gain insights into essential ideas, intuition, and TorDrug tasks. The presentation concludes with discussions on student advisors, questions, causality, and diversity in drug discovery research.
Geometric Deep Learning for Drug Discovery
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#Science
#Life Science
#Drug Discovery
#Social Sciences
#Sociology
#Diversity, Equity, and Inclusion (DEI)
#Diversity
#Mathematics
#Statistics & Probability
#Causality
#Computer Science
#Information Theory
#Mutual Information
#Deep Learning
#Geometric Deep Learning
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