About this Event
210 South Bouquet Street, Pittsburgh, PA 15260
http://sci.pitt.edu/about/events/This colloquium has been postponed until further notice.
Join us as Hongyang Gao, PhD Candidate at Texas A&M University, presents "Graph Neural Networks: A Feature and Structure Learning Approach."
In the real world, many data are naturally represented as graph data such as social networks. Deep learning methods have been very successful in various fields such as computer vision and natural language processing. However, developing deep learning methods on graph data is challenging due to the lack of locality information. In this talk, Gao will present my work on developing deep learning methods on graph data. His work addresses this challenge and significantly advances feature learning and structure learning on graphs in both accuracy and efficiency.
Please let us know if you require an accommodation in order to participate in this event. Accommodations may include live captioning, ASL interpreters, and/or captioned media and accessible documents from recorded events. At least 5 days in advance is recommended.
