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Nov 12, 2022
Zachary Izzo, Jinsung Yoon, Sercan O. Arik, James Zou

* 19 pages, 2 figures 

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Test-Time Adaptation for Visual Document Understanding


Jun 15, 2022
Sayna Ebrahimi, Sercan O. Arik, Tomas Pfister


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Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series


Feb 04, 2022
Sercan O. Arik, Nathanael C. Yoder, Tomas Pfister


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Controlling Neural Networks with Rule Representations


Jun 14, 2021
Sungyong Seo, Sercan O. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister


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Self-Trained One-class Classification for Unsupervised Anomaly Detection


Jun 11, 2021
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O. Arik, Chen-Yu Lee, Tomas Pfister


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Interpretable Sequence Learning for COVID-19 Forecasting


Aug 03, 2020
Sercan O. Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister


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Explaining Deep Neural Networks using Unsupervised Clustering


Jul 16, 2020
Yu-han Liu, Sercan O. Arik


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Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting


Dec 19, 2019
Bryan Lim, Sercan O. Arik, Nicolas Loeff, Tomas Pfister


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On Concept-Based Explanations in Deep Neural Networks


Oct 17, 2019
Chih-Kuan Yeh, Been Kim, Sercan O. Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister


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