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Found 5 papers, 1 papers with code
On Separate Normalization in Self-supervised Transformers
Self-supervised training methods for transformers have demonstrated remarkable performance across various domains.
Multi-objective Deep Data Generation with Correlated Property Control
Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular design.
A Survey on Deep Graph Generation: Methods and Applications
In this paper, we conduct a comprehensive review on the existing literature of deep graph generation from a variety of emerging methods to its wide application areas.
Graph-based Ensemble Machine Learning for Student Performance Prediction
Student performance prediction is a critical research problem to understand the students' needs, present proper learning opportunities/resources, and develop the teaching quality.
Dataset Geography: Mapping Language Data to Language Users
As language technologies become more ubiquitous, there are increasing efforts towards expanding the language diversity and coverage of natural language processing (NLP) systems.
