1 code implementation • 7 Oct 2022 • Rui Wang, Yihe Dong, Sercan Ö. Arik, Rose Yu
Temporal distributional shifts, with underlying dynamics changing over time, frequently occur in real-world time series and pose a fundamental challenge for deep neural networks (DNNs).
1 code implementation • 16 Sep 2022 • Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik, Deniz Yuret, Alper T. Erdogan
In this article, we argue that a straightforward application of information maximization among alternative latent representations of the same input naturally solves the collapse problem and achieves competitive empirical results.
no code implementations • 13 Jun 2022 • Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister
ISL splits the data into different environments, and learns a structure that is invariant to the target across different environments by imposing a consistency constraint.
no code implementations • 5 Jun 2022 • Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister
We introduce a novel framework, Interpretable Mixture of Experts (IME), that provides interpretability for structured data while preserving accuracy.