Machine Learning for a better financial future. 💫
RBC Borealis’ AI Solutions team 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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Unsupervised Event Outlier Detection in Continuous Time
Unsupervised Event Outlier Detection in Continuous Time
S. Nath, K. Y. C. Lui, and S. Liu. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 2024
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LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling
LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling
C. Chen, G. Oliveira, H. Sharifi, and T. Sylvain. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 2024
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Inference, Fast and Slow: Reinterpreting VAEs for OOD Detection
Inference, Fast and Slow: Reinterpreting VAEs for OOD Detection
S. Huang, J. He, and K. Y. C. Lui. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 2024
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Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
Do LLMs Build World Representations? Probing Through the Lens of State Abstraction
Z. Li, Y. Cao, and J. C.K. Cheung. Conference on Neural Information Processing Systems (NeurIPS), 2024
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NeuZip: Memory-Efficient Training and Inference with Dynamic Compression of Neural Networks
NeuZip: Memory-Efficient Training and Inference with Dynamic Compression of Neural Networks
Y. Hao, Y. Cao, and L. Mou. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 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 an RBC Borealis mentorship program for undergraduate students on a mission to solve real problem in their communities using AI. Let’s SOLVE it together.
Open Source Tools
AdverTorch
This toolbox provides machine learning practitioners with the ability to generate private and synthetic data samples from real world data. It currently implements 5 state of the art generative models that can generate differentially private synthetic data.
GitHubLiteTracer
LiteTracer acts as a drop-in replacement for argparse, and it can generate unique identifiers for experiments in addition to what argparse already does. Along with a reverse lookup tool, LiteTracer can trace-back the state of a project that generated any result tagged by the identifier.
GitHubPrivate Synthetic Data Generation
This toolbox provides machine learning practitioners with the ability to generate private and synthetic data samples from real world data.It currently implements 5 state of the art generative models that can generate differentially private synthetic data.
GitHubFellowships
Supporting academic research sits at the core of RBC Borealis. 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.
Careers
Research creates the models that underpin new products for RBC and its 17 million clients. We embrace diversity of perspectives, tenacity, and creative thinking to fundamentally advance what is possible in Machine Learning.
Join the teamCareers
Research creates the models that underpin new products for RBC and its 17 million clients. We embrace diversity of perspectives, tenacity, and creative thinking to fundamentally advance what is possible in Machine Learning.
Join the teamResponsible AI
Responsible AI is key to the future of AI technology, science, development, and adoption. Our RESPECT AI platform contributes knowledge, algorithms, programs, and tooling to help build technology that moves society forward.
Explore the hubResponsible AI
Responsible AI is key to the future of AI technology, science, development, and adoption. Our RESPECT AI platform contributes knowledge, algorithms, programs, and tooling to help build technology that moves society forward.
Explore the hub