Nathanael C. Yoder

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 5

Top Topics

Feature Engineering

Exponential Smoothing

Restricted Boltzmann Machine

Top Venues

npj Digit. Medicine

Trans. Mach. Learn. Res.

Publications

Yihe Dong, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister
Learned Feature Importance Scores for Automated Feature Engineering. CoRR (2024)
Si-An Chen, Chun-Liang Li, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister
TSMixer: An All-MLP Architecture for Time Series Forecast-ing. Trans. Mach. Learn. Res. 2023 (2023)
Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister
Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series. CoRR (2022)
Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021)
Robert D. Chambers, Nathanael C. Yoder
FilterNet: A Many-to-Many Deep Learning Architecture for Time Series Classification. Sensors 20 (9) (2020)