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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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Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost


Oct 16, 2019
Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan O. Arik, Larry S. Davis, Tomas Pfister


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IEG: Robust Neural Network Training to Tackle Severe Label Noise


Oct 13, 2019
Zizhao Zhang, Han Zhang, Sercan O. Arik, Honglak Lee, Tomas Pfister

* v1: first committed preprint, v2: remove small typos in text and figures 

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RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling


Sep 26, 2019
Jinsung Yoon, Sercan O. Arik, Tomas Pfister

* 18 pages, 7 figures, 7 tables 

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TabNet: Attentive Interpretable Tabular Learning


Sep 26, 2019
Sercan O. Arik, Tomas Pfister


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Data Valuation using Reinforcement Learning


Sep 25, 2019
Jinsung Yoon, Sercan O. Arik, Tomas Pfister

* 17 pages, 12 figures, 6 tables 

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Learning to Transfer Learn


Aug 29, 2019
Linchao Zhu, Sercan O. Arik, Yi Yang, Tomas Pfister


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Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks


Feb 17, 2019
Sercan O. Arik, Tomas Pfister


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Fast Spectrogram Inversion using Multi-head Convolutional Neural Networks


Nov 06, 2018
Sercan O. Arik, Heewoo Jun, Gregory Diamos


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Neural Voice Cloning with a Few Samples


Oct 12, 2018
Sercan O. Arik, Jitong Chen, Kainan Peng, Wei Ping, Yanqi Zhou


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Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning


Feb 22, 2018
Wei Ping, Kainan Peng, Andrew Gibiansky, Sercan O. Arik, Ajay Kannan, Sharan Narang, Jonathan Raiman, John Miller

* Published as a conference paper at ICLR 2018. (v3 changed paper title) 

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Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting


Jul 04, 2017
Sercan O. Arik, Markus Kliegl, Rewon Child, Joel Hestness, Andrew Gibiansky, Chris Fougner, Ryan Prenger, Adam Coates

* Accepted to Interspeech 2017 

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Deep Voice: Real-time Neural Text-to-Speech


Mar 07, 2017
Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

* Submitted to ICML 2017 

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