Search Results - "Epshteyn, Arkady"

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan by Arık, Sercan Ö., Shor, Joel, Sinha, Rajarishi, Yoon, Jinsung, Ledsam, Joseph R., Le, Long T., Dusenberry, Michael W., Yoder, Nathanael C., Popendorf, Kris, Epshteyn, Arkady, Euphrosine, Johan, Kanal, Elli, Jones, Isaac, Li, Chun-Liang, Luan, Beth, Mckenna, Joe, Menon, Vikas, Singh, Shashank, Sun, Mimi, Ravi, Ashwin Sura, Zhang, Leyou, Sava, Dario, Cunningham, Kane, Kayama, Hiroki, Tsai, Thomas, Yoneoka, Daisuke, Nomura, Shuhei, Miyata, Hiroaki, Pfister, Tomas

“…The COVID-19 pandemic has highlighted the global need for reliable models of disease spread. We propose an AI-augmented forecast modeling framework that…”
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Generative Prior Knowledge for Discriminative Classification by Epshteyn, A., DeJong, G.

“…We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support…”
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Combining prior knowledge and data: Beyond the Bayesian framework by Epshteyn, Arkady

“…For many tasks such as text categorization and control of robotic systems, state-of-the art learning systems can produce results comparable in accuracy to…”
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BERT for Long Documents: A Case Study of Automated ICD Coding by Afkanpour, Arash, Adeel, Shabir, Bassani, Hansenclever, Epshteyn, Arkady, Fan, Hongbo, Jones, Isaac, Malihi, Mahan, Nauth, Adrian, Sinha, Raj, Woonna, Sanjana, Zamani, Shiva, Kanal, Elli, Fomitchev, Mikhail, Cheung, Donny

“…Transformer models have achieved great success across many NLP problems. However, previous studies in automated ICD coding concluded that these models fail to…”
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Combining prior knowledge and data: Beyond the Bayesian framework by Epshteyn, Arkady

“…For many tasks such as text categorization and control of robotic systems, state-of-the art learning systems can produce results comparable in accuracy to…”
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Interpretable Sequence Learning for COVID-19 Forecasting by Arik, Sercan O, Li, Chun-Liang, Yoon, Jinsung, Sinha, Rajarishi, Epshteyn, Arkady, Le, Long T, Menon, Vikas, Singh, Shashank, Zhang, Leyou, Yoder, Nate, Nikoltchev, Martin, Sonthalia, Yash, Nakhost, Hootan, Kanal, Elli, Pfister, Tomas

“…We propose a novel approach that integrates machine learning into compartmental disease modeling to predict the progression of COVID-19. Our model is…”
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