Results for Generative AI
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NeurIPS 2024 Highlights
NeurIPS 2024 Highlights
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Celebrating the Future of AI: Meet the 2023-2024 RBC Borealis Fellows
Celebrating the Future of AI: Meet the 2023-2024 RBC Borealis Fellows
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NeurIPS 2024
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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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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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RBC maintains strong AI leadership position in financial services
RBC maintains strong AI leadership position in financial services
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Leading in artificial intelligence through education
Leading in artificial intelligence through education
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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
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RESPECT AI: Decarbonizing AI with Dr. Sasha Luccioni, Climate Lead and AI Researcher of Hugging Face
RESPECT AI: Decarbonizing AI with Dr. Sasha Luccioni, Climate Lead and AI Researcher of Hugging Face
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American Banker - Gen AI Integration and Banking Services: A Balancing Act
American Banker - Gen AI Integration and Banking Services: A Balancing Act
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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
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A High-level Overview of Large Language Models
A High-level Overview of Large Language Models
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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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NeurIPS 2022 Recommended Reading List
NeurIPS 2022 Recommended Reading List
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Out-of-distribution II: open-set recognition, OOD labels, and outlier detection
Out-of-distribution II: open-set recognition, OOD labels, and outlier detection
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fAux: Testing Individual Fairness via Gradient Alignment
fAux: Testing Individual Fairness via Gradient Alignment
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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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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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Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Wavelet Flow: Fast Training of High Resolution Normalizing Flows
J. Yu, K. Derpanis, and M. Brubaker. Conference on Neural Information Processing Systems (NeurIPS), 2020
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Evaluating Lossy Compression Rates of Deep Generative Models
Evaluating Lossy Compression Rates of Deep Generative Models
*S. Huang, *A. Makhzani, Y. Cao, and R. Grosse. International Conference on Machine Learning (ICML), 2020
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On Minimax Optimality of GANs for Robust Mean Estimation
On Minimax Optimality of GANs for Robust Mean Estimation
G. W. Ding, R. Huang, Y. Yu, and K. Wu. International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
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Normalizing Flows: An Introduction and Review of Current Methods
Normalizing Flows: An Introduction and Review of Current Methods
I. Kobyzev, S. Prince, and M. Brubaker. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
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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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A Cross-Domain Transferable Neural Coherence Model
A Cross-Domain Transferable Neural Coherence Model
P. Xu, H. Saghir, J. Kang, L. Long, A. J. Bose, and Y. Cao. Association for Computational Linguistics (ACL), 2019
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Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Y. Cao, G. W. Ding, K. Lui, and R. Huang. International Conference on Learning Representations (ICLR), 2018
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Implicit Manifold Learning on Generative Adversarial Networks
Implicit Manifold Learning on Generative Adversarial Networks
K. Lui, Y. Cao, M. Gazeau, and K. S. Zhang. International Conference on Machine Learning Workshop on Implicit Models (ICML), 2017
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NeurIPS 2024 Highlights
NeurIPS 2024 Highlights
-
Celebrating the Future of AI: Meet the 2023-2024 RBC Borealis Fellows
Celebrating the Future of AI: Meet the 2023-2024 RBC Borealis Fellows
-
RBC maintains strong AI leadership position in financial services
RBC maintains strong AI leadership position in financial services
-
Leading in artificial intelligence through education
Leading in artificial intelligence through education
-
RESPECT AI: Decarbonizing AI with Dr. Sasha Luccioni, Climate Lead and AI Researcher of Hugging Face
RESPECT AI: Decarbonizing AI with Dr. Sasha Luccioni, Climate Lead and AI Researcher of Hugging Face
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American Banker - Gen AI Integration and Banking Services: A Balancing Act
American Banker - Gen AI Integration and Banking Services: A Balancing Act
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RESPECT AI: Building AI ethics into the business with Giovanni Leoni of Credo AI
RESPECT AI: Building AI ethics into the business with Giovanni Leoni of Credo AI
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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: Governance for growth with Abhishek Gupta of Montreal AI Ethics Institute
RESPECT AI: Governance for growth with Abhishek Gupta of Montreal AI Ethics Institute
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RESPECT AI: Responsible for future success with Dr. Karina Alexanyan of All Tech is Human
RESPECT AI: Responsible for future success with Dr. Karina Alexanyan of All Tech is Human