40 citations · 50 across the 5 of their papers we have counts for
6 papers
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting
Yang Lin, Irena Koprinska, Mashud Rana
In this paper, we present SSDNet, a novel deep learning approach for time series forecasting. SSDNet combines the Transformer architecture with state space models to provide probab…
ast2vec: Utilizing Recursive Neural Encodings of Python Programs
Benjamin Paaßen, Jessica McBroom, Bryn Jeffries +2
Educational datamining involves the application of datamining techniques to student activity. However, in the context of computer programming, many datamining techniques can not be…
Recursive Tree Grammar Autoencoders
Benjamin Paassen, Irena Koprinska, Kalina Yacef
Machine learning on trees has been mostly focused on trees as input to algorithms. Much less research has investigated trees as output, which has many applications, such as molecul…
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data
Jessica McBroom, Kalina Yacef, Irena Koprinska
Techniques for clustering student behaviour offer many opportunities to improve educational outcomes by providing insight into student learning. However, one important aspect of st…
Tree Echo State Autoencoders with Grammars
Benjamin Paassen, Irena Koprinska, Kalina Yacef
Tree data occurs in many forms, such as computer programs, chemical molecules, or natural language. Unfortunately, the non-vectorial and discrete nature of trees makes it challengi…
A Survey of Automated Programming Hint Generation -- The HINTS Framework
Jessica McBroom, Irena Koprinska, Kalina Yacef
Automated tutoring systems offer the flexibility and scalability necessary to facilitate the provision of high quality and universally accessible programming education. In order to…