Obserwuj
Sjoerd van Steenkiste
Sjoerd van Steenkiste
Research Scientist at Google Research
Zweryfikowany adres z google.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
S van Steenkiste, M Chang, K Greff, J Schmidhuber
International Conference on Learning Representations, 2018
2872018
Towards Accurate Generative Models of Video: A New Metric & Challenges
T Unterthiner*, S van Steenkiste*, K Kurach, R Marinier, M Michalski, ...
arXiv preprint arXiv:1812.01717, 2018
2792018
Neural Expectation Maximization
K Greff*, S van Steenkiste*, J Schmidhuber
Advances in Neural Information Processing Systems 30, 6694--6704, 2017
2702017
On the binding problem in artificial neural networks
K Greff, S Van Steenkiste, J Schmidhuber
arXiv preprint arXiv:2012.05208, 2020
1972020
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
S van Steenkiste, F Locatello, J Schmidhuber, O Bachem
Advances in Neural Information Processing Systems 32, 14222--14235, 2019
1782019
Scaling vision transformers to 22 billion parameters
M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ...
International Conference on Machine Learning, 7480-7512, 2023
1312023
Improving Generalization in Meta Reinforcement Learning using Learned Objectives
L Kirsch, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2020
1192020
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
R Csordás, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2021
632021
Savi++: Towards end-to-end object-centric learning from real-world videos
GF Elsayed*, A Mahendran*, S van Steenkiste*, K Greff, MC Mozer, ...
Advances in Neural Information Processing Systems, 2022
612022
Investigating object compositionality in generative adversarial networks
S Van Steenkiste, K Kurach, J Schmidhuber, S Gelly
Neural Networks 130, 309-325, 2020
53*2020
FVD: A new Metric for Video Generation
T Unterthiner*, S van Steenkiste*, K Kurach, R Marinier, M Michalski, ...
ICLR Workshop on Deep Generative Models for Highly Structured Data, 2019
482019
Object Scene Representation Transformer
MSM Sajjadi, D Duckworth*, A Mahendran*, S van Steenkiste*, F Pavetić, ...
Advances in Neural Information Processing Systems, 2022
452022
Unsupervised Object Keypoint Learning using Local Spatial Predictability
A Gopalakrishnan, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2021
232021
A Wavelet-based Encoding for Neuroevolution
S van Steenkiste, J Koutník, K Driessens, J Schmidhuber
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 517-524, 2016
222016
A Perspective on Objects and Systematic Generalization in Model-Based RL
S van Steenkiste*, K Greff*, J Schmidhuber
ICML Workshop on Generative Modeling and Model-Based Reasoning for Robotics …, 2019
202019
Hierarchical Relational Inference
A Stanić, S van Steenkiste, J Schmidhuber
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9730 …, 2021
182021
Unsupervised learning of temporal abstractions with slot-based transformers
A Gopalakrishnan, K Irie, J Schmidhuber, S van Steenkiste
Neural Computation 35 (4), 593-626, 2023
7*2023
Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames
O Biza, S van Steenkiste, MSM Sajjadi, GF Elsayed, A Mahendran, T Kipf
International Conference on Machine Learning, 2023
52023
Exploring through random curiosity with general value functions
A Ramesh, L Kirsch, S van Steenkiste, J Schmidhuber
Advances in Neural Information Processing Systems, 2022
42022
Test-time adaptation with slot-centric models
M Prabhudesai, A Goyal, S Paul, S van Steenkiste, MSM Sajjadi, ...
International Conference on Machine Learning, 28151--28166, 2023
32023
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20