At Borealis AI, we are driven by our mission to create real-world impact through scientific pursuit.
We’re proud be sponsor The Twelfth International Conference on Learning Representations (ICLR) in Vienna Austria, May 7th to May 11th, 2024. Come meet our team of leading researchers and engineers!
At our booth you’ll hear about the exciting research behind our accepted papers, and our development and use of cutting-edge science to inform business and client transactions, all within a responsible AI framework.
Borealis AI @ #ICLR2024
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AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
Borealis AI’s paper by Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, and Tristan Sylvain has been accepted to ICLR 2024.
🗓️ Tuesday, May 7th @ 10:45 a.m. — 12:45 p.m. CEST
📍 Poster Session 1 – Hall B -
Tree Cross Attention
Borealis AI’s paper by Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, and Mohamed Osama Ahmed has been accepted to ICLR 2024.
🗓️ Wednesday, May 8th @ 10:45 a.m. — 12:45 p.m. CEST
📍 Poster Session 3 – Hall B -
ConR: Contrastive Regularizer for Deep Imbalanced Regression
Borealis AI’s paper by Mahsa Keramati, Lili Meng, and David R. Evans has been accepted to ICLR 2024.
🗓️ Wednesday, May 8th @ 10:45 a.m. — 12:45 p.m. CEST
📍 Poster Session 3 – Hall B -
Ensemble Distillation for Unsupervised Constituency Parsing
Borealis AI’s paper by Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu, Jackie Cheung, and Lili Mou has been accepted to ICLR 2024.
🗓️ Wednesday, May 8th @ 10:45 a.m. — 12:45 p.m. CEST
📍 Poster Session 3 – Hall B
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Conditional Diffusion Models as Self-supervised Learning Backbone for Irregular Time Series at the Workshop on Learning from Time Series for Health
This workshop will bring together machine learning researchers dedicated to advancing the field of time series modeling in healthcare to bring these models closer to deployment.
🗓️ Saturday, May 11th @ 9:00 a.m. — 5:00 p.m. CEST
📍 Strauss 1
Explore our 2024 ICLR publications
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ConR: Contrastive Regularizer for Deep Imbalanced Regression
ConR: Contrastive Regularizer for Deep Imbalanced Regression
M. Keramati, L. Meng, and R. David Evans. International Conference on Learning Representations (ICLR), 2024
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Tree Cross Attention
Tree Cross Attention
L. Feng, F. Tung, H. Hajimirsadeghi, Y. Bengio, and M. O. Ahmed. International Conference on Learning Representations (ICLR), 2024
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Ensemble Distillation for Unsupervised Constituency Parsing
Ensemble Distillation for Unsupervised Constituency Parsing
B. Shayegh, Y. Cao, X. Zhu, J. Chi Kit Cheung, and L. Mou. International Conference on Learning Representations (ICLR), 2024
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AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
Q. Yan, R. Seraj, J. He, L. Meng, and T. Sylvain. International Conference on Learning Representations (ICLR), 2024
Find us at booth 10! 👋
We are researchers, engineers, product and business experts on a mission to forge the future of AI for finance. At Borealis AI, a research institute at RBC, we work on the cutting-edge of AI.
Learn more about our teams-
Tristan Sylvain
Machine Learning Researcher
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Huyen Mori
Early Talent Generalist
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Jiawei (Eric) He
Machine Learning Research Team Lead
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Jaime Trivino
Senior Talent Acquisition Lead
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Dave Evans
Senior Research Engineer
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Mohamed Osama Ahmed
Machine Learning Research Team Lead
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Hossein Hajimirsadeghi
Principal Researcher
News
Borealis AI at ICLR 2024
With ICLR being held in Vienna, Austria, from May 7th to May 11th, 2024, the Borealis AI team is travelling across the globe to showcase our latest research and the cutting-edge work our teams are doing to advance AI in financial services.
Blog
AutoCast++ Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
This blog post is based on our paper accepted to International Conference on Learning Representations (ICLR) 2024. Please refer to the paper AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval for full details.
Blog
Tree Cross Attention
This blog post is based on our paper accepted to International Conference on Learning Representations (ICLR) 2024. Please refer to the paper Tree Cross Attention for full details.
Blog
ConR: Contrastive Regularizer for Deep Imbalanced Regression
This blog post is based on our paper accepted to International Conference on Learning Representations (ICLR) 2024. Please refer to the paper ConR: Contrastive Regularizer for Deep Imbalanced Regression for full details.