Sjoerd van Steenkiste

According to our database, Sjoerd van Steenkiste authored at least 32 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How Does Code Pretraining Affect Language Model Task Performance?

Jackson Petty, Sjoerd van Steenkiste, Tal Linzen

CoRR, 2024

Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models.

Ziyi Wu, Yulia Rubanova, Rishabh Kabra, Drew A. Hudson, Igor Gilitschenski, Yusuf Aytar, Sjoerd van Steenkiste, Kelsey R. Allen, Thomas Kipf

CoRR, 2024

The Impact of Depth on Compositional Generalization in Transformer Language Models.

Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models.

Tiwalayo Eisape, Michael Henry Tessler, Ishita Dasgupta, Fei Sha, Sjoerd van Steenkiste, Tal Linzen

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

DyST: Towards Dynamic Neural Scene Representations on Real-World Videos.

Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DORSal: Diffusion for Object-centric Representations of Scenes et al.

Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Benchmarking Vision Language Models for Cultural Understanding.

Shravan Nayak, Kanishk Jain, Rabiul Awal, Siva Reddy, Sjoerd van Steenkiste, Lisa Anne Hendricks, Karolina Stanczak, Aishwarya Agrawal

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Unsupervised Learning of Temporal Abstractions With Slot-Based Transformers.

Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber, Sjoerd van Steenkiste

Neural Comput., 2023

DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback.

Jiao Sun, Deqing Fu, Yushi Hu, Su Wang, Royi Rassin, Da-Cheng Juan, Dana Alon, Charles Herrmann, Sjoerd van Steenkiste, Ranjay Krishna, Cyrus Rashtchian

CoRR, 2023

The Impact of Depth and Width on Transformer Language Model Generalization.

Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta, Fei Sha, Dan Garrette, Tal Linzen

CoRR, 2023

Sensitivity of Slot-Based Object-Centric Models to their Number of Slots.

Roland S. Zimmermann, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Thomas Kipf, Klaus Greff

CoRR, 2023

Test-time Adaptation with Slot-Centric Models.

Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gaurav Aggarwal, Thomas Kipf, Deepak Pathak, Katerina Fragkiadaki

Proceedings of the International Conference on Machine Learning, 2023

Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames.

Ondrej Biza, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Thomas Kipf

Proceedings of the International Conference on Machine Learning, 2023

Scaling Vision Transformers to 22 Billion Parameters.

Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby

Proceedings of the International Conference on Machine Learning, 2023

2022

Object Scene Representation Transformer.

Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploring through Random Curiosity with General Value Functions.

Aditya A. Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos.

Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

The Design of Matched Balanced Orthogonal Multiwavelets.

Joël M. H. Karel, Sjoerd van Steenkiste, Ralf L. M. Peeters

Frontiers Appl. Math. Stat., 2021

Unsupervised Object Keypoint Learning using Local Spatial Predictability.

Anand Gopalakrishnan, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the 9th International Conference on Learning Representations, 2021

Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks.

Róbert Csordás, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the 9th International Conference on Learning Representations, 2021

Hierarchical Relational Inference.

Aleksandar Stanic, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Investigating object compositionality in Generative Adversarial Networks.

Sjoerd van Steenkiste, Karol Kurach, Jürgen Schmidhuber, Sylvain Gelly

Neural Networks, 2020

On the Binding Problem in Artificial Neural Networks.

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

CoRR, 2020

Improving Generalization in Meta Reinforcement Learning using Learned Objectives.

Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Perspective on Objects and Systematic Generalization in Model-Based RL.

Sjoerd van Steenkiste, Klaus Greff, Jürgen Schmidhuber

CoRR, 2019

Are Disentangled Representations Helpful for Abstract Visual Reasoning?

Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, Olivier Bachem

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

FVD: A new Metric for Video Generation.

Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Towards Accurate Generative Models of Video: A New Metric & Challenges.

Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly

CoRR, 2018

A Case for Object Compositionality in Deep Generative Models of Images.

Sjoerd van Steenkiste, Karol Kurach, Sylvain Gelly

CoRR, 2018

Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions.

Sjoerd van Steenkiste, Michael Chang, Klaus Greff, Jürgen Schmidhuber

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Neural Expectation Maximization.

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

A Wavelet-based Encoding for Neuroevolution.

Sjoerd van Steenkiste, Jan Koutník, Kurt Driessens, Jürgen Schmidhuber

Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016