At Borealis AI, we create real-world impact through scientific pursuit. Borealis AI researches, designs, and builds AI products and technologies that transform RBC businesses and shape the future of finance.
Research Publications
& Tutorials
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Top 20 Tutorials for Machine Learning (ML)
Top 20 Tutorials for Machine Learning (ML)
S. Prince.
Learning And Generalization; Natural Language Processing; Reinforcement Learning
Research Blog
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Introducing ATOM: Borealis AI’s research focus on Asynchronous Temporal Models
Introducing ATOM: Borealis AI’s research focus on Asynchronous Temporal Models
Research
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Few-Shot Learning & Meta-Learning | Tutorial
Few-Shot Learning & Meta-Learning | Tutorial
W. Zi, L. S. Ghoraie, and S. Prince.
Tutorials
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RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Y. Gong, G. Mori, and F. Tung. International Conference on Machine Learning (ICML), 2022
Publication
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Ranking Regularization for Critical Rare Classes: Minimizing False Positives at a High True Positive Rate
Ranking Regularization for Critical Rare Classes: Minimizing False Positives at a High True Positive Rate
*M. Kiarash, H. Zhao, M. Zhai, and F. Tung. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023
Publication
ATOM: Asynchronous Temporal Models
Our researchers aim to build ML models capable of making inferences from asynchronous event sequences. Asynchronous event sequences are ubiquitous in personal banking applications – from various types of transaction data to client interactions with RBC banking services.
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