Machine Learning

On The Specialization of Neural Modules
A number of machine learning models have been proposed with the goal of achieving systematic generalization: the ability to reason …
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Comparing Synthetic Tabular Data Generation Between a Probabilistic Model and a Deep Learning Model for Education Use Cases
The ability to generate synthetic data has a variety of use cases across different domains. In education research, there is a growing …
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Reinforcement Learning in Education: A Multi-Armed Bandit Approach
Advances in reinforcement learning research have demonstrated the ways in which different agent-based models can learn how to optimally …
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Estimation of Body Mass Index from Photographs using Deep Convolutional Neural Networks
Obesity is an important concern in public health, and Body Mass Index is one of the useful, common and convenient measures. However, …
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Defect Detection and Quantification in Electroluminescence Images of Solar PV Modules using U-net Semantic Segmentation
Electroluminescence (EL) images enable defect detection in solar photovoltaic (PV) modules that are otherwise invisible to the naked …
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A Framework for Undergraduate Data Collection Strategies for Student Support Recommendation Systems in Higher Education
Understanding which student support strategies mitigate dropout and improve student retention is an important part of modern higher …
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A Remote Sensing Method to Monitor Water, Aquatic Vegetation, and Invasive Water Hyacinth at National Extents
Diverse freshwater biological communities are threatened by invasive aquatic alien plant (IAAP) invasions and consequently, cost …
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If Dropout Limits Trainable Depth, Does Critical Initialisation Still Matter? A Large-scale Statistical Analysis on ReLU Networks
Recent work in signal propagation theory has shown that dropout limits the depth to which information can propagate through a neural …
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