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Research to help build a better financial future

Our researchers undertake fundamental and applied research and use state-of-the-art ML to address some of the biggest challenges facing the financial services industry today and in the future.

Our widely published research covers a broad range of topics including Reinforcement learning, Natural Language Processing and Time Series Modeling. Our resesarch is made freely available to support the AI community.

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Tails of Lipschitz Triangular Flows
International Conference on Machine Learning (ICML), 2020
Authors: P. Jaini, I. Kobyzev , Y. Yu, M. Brubaker
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On Variational Learning of Controllable Representations for Text without Supervision
International Conference on Machine Learning (ICML), 2020
Authors: P. Xu , J. Cheung , Y. Cao
Abstract Paper BibTeX
Evaluating Lossy Compression Rates of Deep Generative Models
International Conference on Machine Learning (ICML), 2020
Authors: *S. Huang, *A. Makhzani, Y. Cao , R. Grosse
* Denotes equal contribution
Abstract Paper BibTeX
Unsupervised Multilingual Alignment using Wasserstein Barycenter
International Joint Conference on Artificial Intelligence (IJCAI), 2020
Authors: X. Lian, K. Jain, J. Truszkowski , P. Poupart, Y. Yu
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Better Long-Range Dependency by Bootstrapping A Mutual Information Regularizer
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Authors: *Y. Cao , *P. Xu
* Denotes equal contribution
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Multi Type Mean Field Reinforcement Learning
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020
Authors: S. Subramanian, P. Poupart, M. E. Taylor, N. Hegde
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Temporally Extended Auxiliary Tasks
Workshop on Adaptive and Learning Agents (AAMAS), 2020
Authors: C. Sherstan, B. Kartal, P. Hernandez-Leal , M. E. Taylor
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Max-Margin Adversarial Training: Direct Input Space Margin Maximization through Adversarial Training
International Conference on Learning Representations (ICLR), 2020
Authors: G. W. Ding , Y. Sharma, K. Lui , R. Huang
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Representation Learning for Dynamic Graphs: A Survey
Journal of Machine Learning Research (JMLR), 2020
Authors: M. Kazemi , R. Goel, K. Jain, I. Kobyzev , A. Sethi, P. Forsyth , P. Poupart
Abstract Paper BibTeX
Adapting Grad-CAM for Embedding Networks
IEEE Winter Conference on Applications of Computer Vision (WACV), 2020
Authors: L. Chen, J. Chen , H. Hajimirsadeghi , G. Mori
Abstract Paper
Diachronic Embedding for Temporal Knowledge Graph Completion
Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Authors: R. Goel, S. M. Kazemi , M. Brubaker , P. Poupart
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