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SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training


Jun 02, 2021
Gowthami Somepalli, Micah Goldblum, Avi Schwarzschild, C. Bayan Bruss, Tom Goldstein


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Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations


Dec 16, 2020
Rachana Balasubramanian, Samuel Sharpe, Brian Barr, Jason Wittenbach, C. Bayan Bruss


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DLGNet-Task: An End-to-end Neural Network Framework for Modeling Multi-turn Multi-domain Task-Oriented Dialogue


Oct 06, 2020
Oluwatobi O. Olabiyi, Prarthana Bhattarai, C. Bayan Bruss, Zachary Kulis


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Machine Learning for Temporal Data in Finance: Challenges and Opportunities


Sep 11, 2020
Jason Wittenbach, Brian d'Alessandro, C. Bayan Bruss

* KDD '20 ML in Finance Workshop 

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Towards Ground Truth Explainability on Tabular Data


Jul 20, 2020
Brian Barr, Ke Xu, Claudio Silva, Enrico Bertini, Robert Reilly, C. Bayan Bruss, Jason D. Wittenbach

* 6 pages, 5 figures 

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Navigating the Dynamics of Financial Embeddings over Time


Jul 01, 2020
Antonia Gogoglou, Brian Nguyen, Alan Salimov, Jonathan Rider, C. Bayan Bruss


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Quantifying Challenges in the Application of Graph Representation Learning


Jun 18, 2020
Antonia Gogoglou, C. Bayan Bruss, Brian Nguyen, Reza Sarshogh, Keegan E. Hines


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On the Interpretability and Evaluation of Graph Representation Learning


Oct 07, 2019
Antonia Gogoglou, C. Bayan Bruss, Keegan E. Hines

* NeurIPS 2019 Graph Representation Learning workshop 

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Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools


Sep 03, 2019
Anh Truong, Austin Walters, Jeremy Goodsitt, Keegan Hines, C. Bayan Bruss, Reza Farivar


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DeepTrax: Embedding Graphs of Financial Transactions


Jul 16, 2019
C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Antonia Gogoglou, Keegan E. Hines


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Graph Embeddings at Scale


Jul 03, 2019
C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Saurabh Nagrecha, Keegan E. Hines

* Workshop on Mining and Learning with Graphs 2019 

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