1 code implementation • 27 May 2024 • Anand Gopalakrishnan, Aleksandar Stanić, Jürgen Schmidhuber, Michael Curtis Mozer
Current state-of-the-art synchrony-based models encode object bindings with complex-valued activations and compute with real-valued weights in feedforward architectures.
no code implementations • 3 Jan 2024 • Aleksandar Stanić, Sergi Caelles, Michael Tschannen
Recently, these models achieved great performance on tasks such as compositional visual question answering, visual grounding, and video temporal reasoning.
1 code implementation • 20 Sep 2023 • Aleksandar Stanić, Dylan Ashley, Oleg Serikov, Louis Kirsch, Francesco Faccio, Jürgen Schmidhuber, Thomas Hofmann, Imanol Schlag
We introduce an experimental protocol that enables model comparisons based on equivalent compute, measured in accelerator hours.
no code implementations • 26 May 2023 • Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
What should be the social structure of an NLSOM?
1 code implementation • NeurIPS 2023 • Aleksandar Stanić, Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber
Current state-of-the-art object-centric models use slots and attention-based routing for binding.
1 code implementation • 5 Aug 2022 • Aleksandar Stanić, Yujin Tang, David Ha, Jürgen Schmidhuber
We show that current agents struggle to generalize, and introduce novel object-centric agents that improve over strong baselines.
1 code implementation • ICLR 2021 • Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann
We show that augmenting the decoder of a hierarchical VAE by spatial dependency layers considerably improves density estimation over baseline convolutional architectures and the state-of-the-art among the models within the same class.
no code implementations • 7 Oct 2020 • Aleksandar Stanić, Sjoerd van Steenkiste, Jürgen Schmidhuber
Common-sense physical reasoning in the real world requires learning about the interactions of objects and their dynamics.
no code implementations • 11 Oct 2019 • Aleksandar Stanić, Jürgen Schmidhuber
Traditional sequential multi-object attention models rely on a recurrent mechanism to infer object relations.
no code implementations • 26 May 2016 • Thomas Wiatowski, Michael Tschannen, Aleksandar Stanić, Philipp Grohs, Helmut Bölcskei
First steps towards a mathematical theory of deep convolutional neural networks for feature extraction were made---for the continuous-time case---in Mallat, 2012, and Wiatowski and B\"olcskei, 2015.