121 citations · 187 across the 11 of their papers we have counts for
11 papers
Leaping Through Time with Gradient-based Adaptation for Recommendation
Nuttapong Chairatanakul, Hoang NT, Xin Liu +1
Modern recommender systems are required to adapt to the change in user preferences and item popularity. Such a problem is known as the temporal dynamics problem, and it is one of t…
Natural Image Reconstruction from fMRI using Deep Learning: A Survey
Zarina Rakhimberdina, Quentin Jodelet, Xin Liu +1
With the advent of brain imaging techniques and machine learning tools, much effort has been devoted to building computational models to capture the encoding of visual information…
Simplifying approach to Node Classification in Graph Neural Networks
Sunil Kumar Maurya, Xin Liu, Tsuyoshi Murata
Graph Neural Networks have become one of the indispensable tools to learn from graph-structured data, and their usefulness has been shown in wide variety of tasks. In recent years,…
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph
Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee +2
In cross-lingual text classification, it is required that task-specific training data in high-resource source languages are available, where the task is identical to that of a low-…
Improving Graph Neural Networks with Simple Architecture Design
Sunil Kumar Maurya, Xin Liu, Tsuyoshi Murata
Graph Neural Networks have emerged as a useful tool to learn on the data by applying additional constraints based on the graph structure. These graphs are often created with assume…
Balanced softmax cross-entropy for incremental learning with and without memory
Quentin Jodelet, Xin Liu, Tsuyoshi Murata
When incrementally trained on new classes, deep neural networks are subject to catastrophic forgetting which leads to an extreme deterioration of their performance on the old class…