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DTSTAMP:20250801T021215Z
DESCRIPTION:Jian Tang (HEC Montreal)\n	October 20th\, 12-1pm \n	Zoom Link: ht
 tps/mcgill.zoom.us/j/91589192037\n\nTitle: Graph Representation Learning a
 nd Applications to Drug Discovery.\n\nAbstract: Graphs\, a general type of
  data structures for capturing interconnected objects\, are ubiquitous in 
 a variety of disciplines and domains. In this talk\, I will introduce our 
 work on graph representation learning and applications to drug discovery. 
 In the first part\, I will introduce our work on graph embeddings includin
 g learning node representations (LINE\, WWW’15)\, extremely low-dimensiona
 l node representation learning for graph and high-dimensional data visuali
 zation (LargeVis\, WWW’16)\, knowledge graph embedding (RotatE\, ICLR’19)\
 , and a general and high-performance graph embedding system (GraphVite\, W
 WW’19\, https://graphvite.io/). In the second part\, I will introduce our 
 recent work on graph representation learning for drug discovery including 
 an unsupervised and semi-supervised approach for learning graph representa
 tions for molecule properties prediction and a new generative model for mo
 lecular graph generation and optimization.\n
DTSTART:20201014T164500Z
DTEND:20201014T164500Z
SUMMARY:QLS Seminar Series - Jian Tang
URL:/qls/channels/event/qls-seminar-series-jian-tang-3
 25339
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