PLDI 2020 (series) / MAPL 2020 (series) / MAPL /
LambdaNet: Probabilistic Type Inference using Graph Neural Networks
Tue 16 Jun 2020 09:30 - 10:00 at MAPL live stream - Graph Neural Networks for Program Reasoning Chair(s): Ke Wang
Isil Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her main research interests are program analysis, verification, and synthesis as well as their applications in security and databases. She is the recipient of a Sloan Fellowship and an NSF CAREER award, and, prior to joining UT, she got all her degrees (BS, MS, and PhD) from Stanford University. Outside of work, she can be found hiking, scuba diving, and taking photographs in various parts of the world.
Tue 16 JunDisplayed time zone: Pacific Time (US & Canada) change
Tue 16 Jun
Displayed time zone: Pacific Time (US & Canada) change
08:00 - 10:00 | |||
08:00 30mTalk | Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs MAPL Elizabeth Dinella University of Pennsylvania | ||
08:30 60mTutorial | A Gentle Tutorial on Graph Neural Networks and Its Application to Programming Languages MAPL Yizhou Sun UCLA | ||
09:30 30mTalk | LambdaNet: Probabilistic Type Inference using Graph Neural Networks MAPL Işıl Dillig University of Texas at Austin, USA |