88 citations · 98 across the 3 of their papers we have counts for
6 papers
Relational dynamic memory networks
Trang Pham, Truyen Tran, Svetha Venkatesh
Neural networks excel in detecting regular patterns but are less successful in representing and manipulating complex data structures, possibly due to the lack of an external memory…
A deep tree-based model for software defect prediction
Hoa Khanh Dam, Trang Pham, Shien Wee Ng +5
Defects are common in software systems and can potentially cause various problems to software users. Different methods have been developed to quickly predict the most likely locati…
Graph Memory Networks for Molecular Activity Prediction
Trang Pham, Truyen Tran, Svetha Venkatesh
Molecular activity prediction is critical in drug design. Machine learning techniques such as kernel methods and random forests have been successful for this task. These models req…
Graph Classification via Deep Learning with Virtual Nodes
Trang Pham, Truyen Tran, Hoa Dam +1
Learning representation for graph classification turns a variable-size graph into a fixed-size vector (or matrix). Such a representation works nicely with algebraic manipulations.…
Automatic feature learning for vulnerability prediction
Hoa Khanh Dam, Truyen Tran, Trang Pham +3
Code flaws or vulnerabilities are prevalent in software systems and can potentially cause a variety of problems including deadlock, information loss, or system failure. A variety o…
One Size Fits Many: Column Bundle for Multi-X Learning
Trang Pham, Truyen Tran, Svetha Venkatesh
Much recent machine learning research has been directed towards leveraging shared statistics among labels, instances and data views, commonly referred to as multi-label, multi-inst…