Results for Computer Vision
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ATOM: Attention Mixer for Efficient Dataset Distillation
ATOM: Attention Mixer for Efficient Dataset Distillation
*S. Khaki, *A. Sajedi, K. Wang, L. Z. Liu, Y. A. Lawryshyn, and K. N. Plataniotis. Oral presentation at The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024
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NeurIPS 2023 Recommended Reading List
NeurIPS 2023 Recommended Reading List
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Unlocking Potential: Get to Know RBC Borealis's Fall 2023 Research Interns and Engineering Co-op Students
Unlocking Potential: Get to Know RBC Borealis's Fall 2023 Research Interns and Engineering Co-op Students
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What Constitutes Good Contrastive Learning in Time-Series Forecasting?
What Constitutes Good Contrastive Learning in Time-Series Forecasting?
C. Zhang, Q. Yan, L. Meng, and T. Sylvain. Workshop at International Joint Conference on Artificial Intelligence (IJCAI), 2023
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AI as a force for good: Let’s SOLVE it Demo Day
AI as a force for good: Let’s SOLVE it Demo Day
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RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
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NeurIPS 2023 Recommended Reading List
NeurIPS 2023 Recommended Reading List
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RBC Borealis at International Conference on Learning Representations (ICLR): Machine Learning for a better financial future
RBC Borealis at International Conference on Learning Representations (ICLR): Machine Learning for a better financial future
Learning And Generalization; Natural Language Processing; Time series Modelling
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Introducing ATOM: RBC Borealis’s research focus on Asynchronous Temporal Models
Introducing ATOM: RBC Borealis’s research focus on Asynchronous Temporal Models
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Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
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Adaptive Models of Non-Stationary Dynamics in Capital Markets
Adaptive Models of Non-Stationary Dynamics in Capital Markets
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Self-supervised Learning in Time-Series Forecasting — A Contrastive Learning Approach
Self-supervised Learning in Time-Series Forecasting — A Contrastive Learning Approach
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RBC Borealis at the Neural Information Processing Systems (NeurIPS) Conference 2022
RBC Borealis at the Neural Information Processing Systems (NeurIPS) Conference 2022
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NeurIPS 2022 Recommended Reading List
NeurIPS 2022 Recommended Reading List
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ATOM: Attention Mixer for Efficient Dataset Distillation
ATOM: Attention Mixer for Efficient Dataset Distillation
*S. Khaki, *A. Sajedi, K. Wang, L. Z. Liu, Y. A. Lawryshyn, and K. N. Plataniotis. Oral presentation at The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024
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What Constitutes Good Contrastive Learning in Time-Series Forecasting?
What Constitutes Good Contrastive Learning in Time-Series Forecasting?
C. Zhang, Q. Yan, L. Meng, and T. Sylvain. Workshop at International Joint Conference on Artificial Intelligence (IJCAI), 2023
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Towards Better Selective Classification
Towards Better Selective Classification
L. Feng, M. O. Ahmed, H. Hajimirsadeghi, and A. Abdi. International Conference on Learning Representations (ICLR), 2023
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Gumbel-Softmax Selective Networks
Gumbel-Softmax Selective Networks
M. Salem, M. O. Ahmed, F. Tung, and G. Oliveira. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 2022
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Training a Vision Transformer from scratch in less than 24 hours with 1 GPU
Training a Vision Transformer from scratch in less than 24 hours with 1 GPU
S. Irandoust, T. Durand, Y. Rakhmangulova, W. Zi, and H. Hajimirsadeghi. Workshop at Conference on Neural Information Processing Systems (NeurIPS), 2022
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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
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Learning User Representations for Open Vocabulary Image Hashtag Prediction
Learning User Representations for Open Vocabulary Image Hashtag Prediction
T. Durand. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2020
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Generating Videos of Zero-Shot Compositions of Actions and Objects
Generating Videos of Zero-Shot Compositions of Actions and Objects
M. Nawhal, M. Zhai, A. Lehrmann, L. Sigal, and G. Mori. The European Conference on Computer Vision (ECCV), 2019
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Noise Flow: Noise Modeling with Conditional Normalizing Flows
Noise Flow: Noise Modeling with Conditional Normalizing Flows
A. Abdelhamed, M. Brubaker, and M. S. Brown. International Conference on Computer Vision (ICCV), 2019
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Similarity-Preserving Knowledge Distillation
Similarity-Preserving Knowledge Distillation
F. Tung, and G. Mori. International Conference on Computer Vision (ICCV), 2019
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LayoutVAE: Stochastic Scene Layout Generation from a Label Set
LayoutVAE: Stochastic Scene Layout Generation from a Label Set
A. Jyothi, T. Durand, J. He, L. Sigal, and G. Mori. International Conference on Computer Vision (ICCV), 2019
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Lifelong GAN: Continual Learning for Conditional Image Generation
Lifelong GAN: Continual Learning for Conditional Image Generation
*M. Zhai, *L. Chen, F. Tung, J. He, M. Nawhal, and G. Mori. International Conference on Computer Vision (ICCV), 2019
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Unlocking Potential: Get to Know RBC Borealis's Fall 2023 Research Interns and Engineering Co-op Students
Unlocking Potential: Get to Know RBC Borealis's Fall 2023 Research Interns and Engineering Co-op Students
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AI as a force for good: Let’s SOLVE it Demo Day
AI as a force for good: Let’s SOLVE it Demo Day
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RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
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The RBC Borealis 2023 Machine Learning Researcher Internship and Engineering Co-op Programs: Developing Tomorrow’s AI Leaders
The RBC Borealis 2023 Machine Learning Researcher Internship and Engineering Co-op Programs: Developing Tomorrow’s AI Leaders
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2022 Report: Canadian businesses’ use of AI
2022 Report: Canadian businesses’ use of AI
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Driving Innovation in Financial Services: RBC Borealis’s Research Areas of Focus
Driving Innovation in Financial Services: RBC Borealis’s Research Areas of Focus
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AI as a Personal Banker
AI as a Personal Banker
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RBC Borealis Graduate Fellowships - The Class of 2020
RBC Borealis Graduate Fellowships - The Class of 2020