Jialin Yu's Outputs (2)

A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data (2021)
Presentation / Conference Contribution
Sun, Z., Harit, A., Yu, J., Cristea, A., & Al Moubayed, N. (2021, July). A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data. Presented at IEEE International Joint Conference on Neural Network (IJCNN2021), Virtual

This research focuses on semi-supervised classification tasks, specifically for graph-structured data under datascarce situations. It is known that the performance of conventional supervised graph convolutional models is mediocre at classification ta... Read More about A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data.

Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums (2021)
Presentation / Conference Contribution
Yu, J., Alrajhi, L., Harit, A., Sun, Z., Cristea, A. I., & Shi, L. (2021, June). Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual

Massive Open Online Courses (MOOCs) have become a popular choice for e-learning thanks to their great flexibility. However, due to large numbers of learners and their diverse backgrounds, it is taxing to offer real-time support. Learners may post the... Read More about Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums.