Machine Learning for a better financial future. 💫
Borealis AI conducts research in artificial intelligence for financial services. We are a large team of researchers with backgrounds across artificial intelligence including computer vision, machine learning, and natural language processing, with PhDs in computer science, physics, computational finance, mathematics and more.
The research team undertakes fundamental and applied research, publishes papers, and works with large-scale datasets, deriving impactful machine learning models in collaboration with machine learning product owners and software engineers who help bring the research and prototypes to life.
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EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation
EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation
Y. Wen, B. Shayegh, C. Huang, Y. Cao, and L. Mou. Workshop at International Conference on Machine Learning (ICML), 2024
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Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
A. Vani, F. Tung, G. Oliveira, and H. Sharifi. International Conference on Machine Learning (ICML), 2024
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Memory Efficient Neural Processes via Constant Memory Attention Block
Memory Efficient Neural Processes via Constant Memory Attention Block
L. Feng, F. Tung, H. Hajimirsadeghi, Y. Bengio, and M. O. Ahmed. International Conference on Machine Learning (ICML), 2024
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Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Y. Hao, Y. Cao, and L. Mou. International Conference on Machine Learning (ICML), 2024
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Conditional Diffusion Models as Self-supervised Learning Backbone for Irregular Time Series
Conditional Diffusion Models as Self-supervised Learning Backbone for Irregular Time Series
Hamed Shirzad, R. Deng, H. Zhao, and F. Tung. Workshop at International Conference on Representation Learning (ICLR), 2024
North Star
Research Areas
We focus on a set of challenging North Star research problems: Asynchronous Temporal Models, Non-Cooperative Learning in Competing Markets, and Machine Intelligence beyond Predictive ML.
Let’s SOLVE It
New and diverse perspectives, awareness of challenges specific to local communities, and commitment to making a difference are needed today more than ever. Let’s SOLVE it is a Borealis AI mentorship program for undergraduate students on a mission to solve real problem in their communities using AI. Let’s SOLVE it together.
Fellowships
Supporting academic research sits at the core of Borealis AI. Our Fellowship program supports graduate students’ research and career goals, helping advance the science of AI.
Internships
Research interns work with all our teams, collaborate with RBC on large-scale projects, and publish original research.