1 code implementation • 23 May 2025 • Yujin Jeong, Arnas Uselis, Seong Joon Oh, Anna Rohrbach
To address this, we present a comprehensive study of the discriminative capabilities of diffusion classifiers on a wide range of compositional tasks.
1 code implementation • 5 Feb 2025 • Darina Koishigarina, Arnas Uselis, Seong Joon Oh
We find that the correct attribute-object binding information is already present in individual text and image modalities.
1 code implementation • 11 Apr 2022 • Mantas Lukoševičius, Arnas Uselis
We propose an elegant straightforward alternative approach where instead the RNN is in effect resampled in time to match the time of the data or the task at hand.
1 code implementation • 19 Jun 2020 • Mantas Lukoševičius, Arnas Uselis
The second level of optimization also makes the (ii) part remain constant irrespective of large $k$, as long as the dimension of the output is low.
1 code implementation • 12 May 2020 • Arnas Uselis, Mantas Lukoševičius, Lukas Stasytis
They can be added to any convolutional layers, easily end-to-end trained, introduce minimal additional complexity, and let CNNs retain most of their benefits to the extent that they are needed.
1 code implementation • 22 Aug 2019 • Mantas Lukoševičius, Arnas Uselis
Thus in many situations $k$-fold cross-validation of ESNs can be done for virtually the same time complexity as a simple single split validation.