TSMixer: An All-MLP Architecture for Time Series Forecasting

2 code implementations • 10 Mar 2023 • Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan O. Arik, Tomas Pfister

Extending them, in this paper, we investigate the capabilities of linear models for time-series forecasting and present Time-Series Mixer (TSMixer), a novel architecture designed by stacking multi-layer perceptrons (MLPs).

Time Series Time Series Forecasting

Interpretable Sequence Learning for COVID-19 Forecasting

no code implementations • NeurIPS 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

We propose a novel approach that integrates machine learning into compartmental disease modeling to predict the progression of COVID-19.